Bio

Stephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University, and a member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.

Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).

Professor Boyd is the author of many research articles and four books: Introduction to Applied Linear Algebra: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with El Ghaoui, Feron, and Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.

He has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, for excellence in computational mathematical programming. In 2023, he was given the AACC Richard E. Bellman Control Heritage Award, the highest recognition of professional achievement for U.S. control systems engineers and scientists. He is a Fellow of the IEEE, SIAM, INFORMS, and IFAC, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, a foreign member of the Chinese Academy of Engineering, and a foreign member of the National Academy of Engineering of Korea. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.

He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education. In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization."

Academic Appointments

Administrative Appointments

  • Chair, Department of Electrical Engineering (2018 - Present)

Honors & Awards

  • Beal-Orchard-Hays Prize, Mathematical Optimization Society (2024)
  • Richard E. Bellman Control Heritage Award, American Automatic Control Council (2023)
  • Fellow, International Federation of Automatic Control (2022)
  • Foreign member, National Academy of Engineering of Korea (2020)
  • Athanasios Papoulis Society Award, European Association for Signal Processing (EURASIP) (2019)
  • Foreign member, Chinese Academy of Engineeering (2017)
  • Honorary PhD, University Catholique de Louvain (2017)
  • James H. Mulligan, Jr. Education Medal, IEEE (2017)
  • Fellow, INFORMS (2016)
  • Walter J. Gores teaching award, Stanford (2016)
  • Fellow, SIAM (2015)
  • Member, National Academy of Engineering (2014)
  • Saul Gass Award, INFORMS (2014)
  • Control Systems Award, IEEE (2013)
  • Beal-Orchard-Hays Prize, Mathematical Optimization Society (2012)
  • Honorary PhD, Royal Institute of Technology (KTH), Stockholm (2006)
  • Section lecture, International Congress of Mathematicians (2006)
  • John R. Ragazzini Award, Automatic Control Council (2003)
  • Fellow, IEEE Control Systems Society (1999)
  • Hugo Schuck Award, IEEE Control Systems Society (1999)
  • Perrin Award for Undergraduate Teaching, Stanford University (1994)
  • Distinguished Lecturer, IEEE Control System Society (1993)
  • Donald P. Eckman Award, IEEE Control Systems Society (1992)
  • Graduate Teaching Award, ASSU (1991)
  • Presidential Young Investigator Award, National Science Foundation (1986)

Professional Education

  • PhD, UC Berkeley, EECS (1985)
  • BA, Harvard University, Mathematics (1980)

Contact

  • Academic
    Stephen.Boyd@stanford.edu
    University - Faculty Department: Electrical Engineering Position: Professor
    • PACKARD BLDG. #254
    • Stanford,  California  94305-9510 

Additional Info

Links

2024-25 Courses

All Publications

  • Approximate sequential optimization for informative path planning ROBOTICS AND AUTONOMOUS SYSTEMS Ott, J., Kochenderfer, M. J., Boyd, S. 2024; 182

    View details for DOI 10.1016/j.robot.2024.104814

    View details for Web of Science ID 001333214800001

  • Finding moving-band statistical arbitrages via convex-concave optimization OPTIMIZATION AND ENGINEERING Johansson, K., Schmelzer, T., Boyd, S. 2024

    View details for DOI 10.1007/s11081-024-09933-0

    View details for Web of Science ID 001343528500001

  • Efficient Shapley performance attribution for least-squares regression STATISTICS AND COMPUTING Bell, L., Devanathan, N., Boyd, S. 2024; 34 (5)

    View details for DOI 10.1007/s11222-024-10459-9

    View details for Web of Science ID 001262282900001

  • Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Luxenberg, E., Malik, D., Li, Y., Singh, A., Boyd, S. 2024

    View details for DOI 10.1007/s10957-024-02491-6

    View details for Web of Science ID 001283260400001

  • Markowitz Portfolio Construction at Seventy JOURNAL OF PORTFOLIO MANAGEMENT Boyd, S., Johansson, K., Kahn, R., Schiele, P., Schmelzer, T. 2024; 50 (8): 117-160

    View details for Web of Science ID 001272825200011

  • Robust Bond Portfolio Construction via Convex-Concave Saddle Point Optimization JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Luxenberg, E., Schiele, P., Boyd, S. 2024

    View details for DOI 10.1007/s10957-024-02436-z

    View details for Web of Science ID 001220929000001

  • Polyak Minorant Method for Convex Optimization JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Devanathan, N., Boyd, S. 2024

    View details for DOI 10.1007/s10957-024-02412-7

    View details for Web of Science ID 001194609600001

  • Portfolio Optimization with Cumulative Prospect Theory Utility via Convex Optimization COMPUTATIONAL ECONOMICS Luxenberg, E., Schiele, P., Boyd, S. 2024

    View details for DOI 10.1007/s10614-024-10556-x

    View details for Web of Science ID 001159490000001

  • Compact Model Parameter Extraction via Derivative-Free Optimization IEEE ACCESS Martinez, R., Iwamoto, M., Woo, K., Bian, Z., Tinti, R., Boyd, S., Chowdhury, S. 2024; 12: 123224-123235

    View details for DOI 10.1109/ACCESS.2024.3453198

    View details for Web of Science ID 001311188600001

  • Fast Path Planning Through Large Collections of Safe Boxes IEEE TRANSACTIONS ON ROBOTICS Marcucci, T., Nobel, P., Tedrake, R., Boyd, S. 2024; 40: 3795-3811

    View details for DOI 10.1109/TRO.2024.3434168

    View details for Web of Science ID 001291896800003

  • Implementation of an oracle-structured bundle method for distributed optimization OPTIMIZATION AND ENGINEERING Parshakova, T., Zhang, F., Boyd, S. 2023

    View details for DOI 10.1007/s11081-023-09859-z

    View details for Web of Science ID 001109181100001

  • Value-gradient iteration with quadratic approximate value functions ANNUAL REVIEWS IN CONTROL Yang, A., Boyd, S. 2023; 56

    View details for DOI 10.1016/j.arcontrol.2023.100917

    View details for Web of Science ID 001112281100001

  • Portfolio construction with Gaussian mixture returns and exponential utility via convex optimization OPTIMIZATION AND ENGINEERING Luxenberg, E., Boyd, S. 2023

    View details for DOI 10.1007/s11081-023-09814-y

    View details for Web of Science ID 001037322900001

  • Bounds on Efficiency Metrics in Photonics ACS PHOTONICS Angeris, G., Diamandis, T., Vuckovic, J., Boyd, S. P. 2023

    View details for DOI 10.1021/acsphotonics.3c00023

    View details for Web of Science ID 001024824200001

  • Convex optimization over risk-neutral probabilities OPTIMIZATION AND ENGINEERING Barratt, S., Tuck, J., Boyd, S. 2023

    View details for DOI 10.1007/s11081-023-09802-2

    View details for Web of Science ID 000976821600001

  • PV Fleet Modeling via Smooth Periodic Gaussian Copula Ogut, M. G., Meyers, B., Boyd, S. P., IEEE IEEE. 2023

    View details for DOI 10.1109/PVSC48320.2023.10359991

    View details for Web of Science ID 001151676200467

  • Tractable Evaluation of Stein's Unbiased Risk Estimate With Convex Regularizers IEEE TRANSACTIONS ON SIGNAL PROCESSING Nobel, P., Candes, E., Boyd, S. 2023; 71: 4330-4341

    View details for DOI 10.1109/TSP.2023.3323046

    View details for Web of Science ID 001123968900002

  • Signal Decomposition Using Masked Proximal Operators FOUNDATIONS AND TRENDS IN SIGNAL PROCESSING Meyers, B. E., Boyd, S. P. 2023; 17 (1): 1-78

    View details for DOI 10.1561/200000122

    View details for Web of Science ID 000994685200001

  • RSQP: Problem-specific Architectural Customization for Accelerated Convex Quadratic Optimization Wang, M., McInerney, I., Stellato, B., Boyd, S., So, H., ACM ASSOC COMPUTING MACHINERY. 2023: 1026-1037

    View details for DOI 10.1145/3579371.3589108

    View details for Web of Science ID 001098723900073

  • Confidence Bands for a Log-Concave Density JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS Walther, G., Ali, A., Shen, X., Boyd, S. 2022; 31 (4): 1426-1438

    View details for DOI 10.1080/10618600.2022.2076688

    View details for Web of Science ID 000888844200039

  • Computing tighter bounds on the n-queens constant via Newton's method OPTIMIZATION LETTERS Nobel, P., Agrawal, A., Boyd, S. 2022

    View details for DOI 10.1007/s11590-022-01933-2

    View details for Web of Science ID 000854857100001

  • Covariance prediction via convex optimization OPTIMIZATION AND ENGINEERING Barratt, S., Boyd, S. 2022

    View details for DOI 10.1007/s11081-022-09765-w

    View details for Web of Science ID 000849470800001

  • A general optimization framework for dynamic time warping OPTIMIZATION AND ENGINEERING Deriso, D., Boyd, S. 2022

    View details for DOI 10.1007/s11081-022-09738-z

    View details for Web of Science ID 000842420700001

  • Multi-period liability clearing via convex optimal control OPTIMIZATION AND ENGINEERING Barratt, S., Boyd, S. 2022

    View details for DOI 10.1007/s11081-022-09737-0

    View details for Web of Science ID 000819912100001

  • Confidence Bands for a Log-Concave Density JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS Walther, G., Ali, A., Shen, X., Boyd, S. 2022

    View details for DOI 10.1080/01621459.2022.2076688

    View details for Web of Science ID 000815471000001

  • Fitting feature-dependent Markov chains JOURNAL OF GLOBAL OPTIMIZATION Barratt, S., Boyd, S. 2022

    View details for DOI 10.1007/s10898-022-01198-0

    View details for Web of Science ID 000811964900001

  • Operator splitting for adaptive radiation therapy with nonlinear health dynamics OPTIMIZATION METHODS & SOFTWARE Fu, A., Xing, L., Boyd, S. 2022

    View details for DOI 10.1080/10556788.2022.2078824

    View details for Web of Science ID 000804607500001

  • Allocation of fungible resources via a fast, scalable price discovery method MATHEMATICAL PROGRAMMING COMPUTATION Agrawal, A., Boyd, S., Narayanan, D., Kazhamiaka, F., Zaharia, M. 2022

    View details for DOI 10.1007/s12532-022-00220-6

    View details for Web of Science ID 000784049700001

  • Minimizing oracle-structured composite functions OPTIMIZATION AND ENGINEERING Shen, X., Ali, A., Boyd, S. 2022

    View details for DOI 10.1007/s11081-021-09705-0

    View details for Web of Science ID 000741580400001

  • Embedded Code Generation With CVXPY IEEE CONTROL SYSTEMS LETTERS Schaller, M., Banjac, G., Diamond, S., Agrawal, A., Stellato, B., Boyd, S. 2022; 6: 2653-2658

    View details for DOI 10.1109/LCSYS.2022.3173209

    View details for Web of Science ID 000797431900004

  • Strategic Asset Allocation with Illiquid Alternatives Luxenberg, E., Boyd, S., van Beek, M., Cao, W., Kochenderfer, M., ACM ASSOC COMPUTING MACHINERY. 2022: 249-256

    View details for DOI 10.1145/3533271.3561769

    View details for Web of Science ID 001103234000030

  • PORTFOLIO PERFORMANCE ATTRIBUTION VIA SHAPLEY VALUE JOURNAL OF INVESTMENT MANAGEMENT Moehle, N., Boyd, S., Ang, A. 2022; 20 (3): 33-52

    View details for Web of Science ID 000834737700004

  • Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization IEEE ACCESS Shlezinger, N., Eldar, Y. C., Boyd, S. P. 2022; 10: 115384-115398

    View details for DOI 10.1109/ACCESS.2022.3218802

    View details for Web of Science ID 000880586800001

  • A Certainty Equivalent Merton Problem IEEE CONTROL SYSTEMS LETTERS Moehle, N., Boyd, S. 2022; 6: 1478-1483

    View details for DOI 10.1109/LCSYS.2021.3111534

    View details for Web of Science ID 000697816400001

  • Stochastic Control With Affine Dynamics and Extended Quadratic Costs IEEE TRANSACTIONS ON AUTOMATIC CONTROL Barratt, S., Boyd, S. 2022; 67 (1): 320-335

    View details for DOI 10.1109/TAC.2021.3064535

    View details for Web of Science ID 000735567400026

  • Pareto Optimal Projection Search (POPS): Automated Radiation Therapy Treatment Planning by Direct Search of the Pareto Surface IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Huang, C., Yang, Y., Panjwani, N., Boyd, S., Xing, L. 2021; 68 (10): 2907-2917

    Abstract

    Radiation therapy treatment planning is a time-consuming, iterative process with potentially high inter-planner variability. Fully automated treatment planning processes could reduce a planner's active treatment planning time and remove inter-planner variability, with the potential to tremendously improve patient turnover and quality of care. In developing fully automated algorithms for treatment planning, we have two main objectives: to produce plans that are 1) Pareto optimal and 2) clinically acceptable. Here, we propose the Pareto optimal projection search (POPS) algorithm, which provides a general framework for directly searching the Pareto front.Our POPS algorithm is a novel automated planning method that combines two main search processes: 1) gradient-free search in the decision variable space and 2) projection of decision variables to the Pareto front using the bisection method. We demonstrate the performance of POPS by comparing with clinical treatment plans. As one possible quantitative measure of treatment plan quality, we construct a clinical acceptability scoring function (SF) modified from the previously developed general evaluation metric (GEM).On a dataset of 21 prostate cases collected as part of clinical workflow, our proposed POPS algorithm produces Pareto optimal plans that are clinically acceptable in regards to dose conformity, dose homogeneity, and sparing of organs-at-risk.Our proposed POPS algorithm provides a general framework for fully automated treatment planning that achieves clinically acceptable dosimetric quality without requiring active planning from human planners.Our fully automated POPS algorithm addresses many key limitations of other automated planning approaches, and we anticipate that it will substantially improve treatment planning workflow.

    View details for DOI 10.1109/TBME.2021.3055822

    View details for Web of Science ID 000697820800006

    View details for PubMedID 33523802

  • Learning Convex Optimization Models IEEE-CAA JOURNAL OF AUTOMATICA SINICA Agrawal, A., Barratt, S., Boyd, S. 2021; 8 (8): 1355-1364

    View details for DOI 10.1109/JAS.2021.1004075

    View details for Web of Science ID 000669496100001

  • Convex restrictions in physical design. Scientific reports Angeris, G., Vuckovic, J., Boyd, S. 2021; 11 (1): 12976

    Abstract

    In a physical design problem, the designer chooses values of some physical parameters, within limits, to optimize the resulting field. We focus on the specific case in which each physical design parameter is the ratio of two field variables. This form occurs for photonic design with real scalar fields, diffusion-type systems, and others. We show that such problems can be reduced to a convex optimization problem, and therefore efficiently solved globally, given the sign of an optimal field at every point. This observation suggests a heuristic, in which the signs of the field are iteratively updated. This heuristic appears to have good practical performance on diffusion-type problems (including thermal design and resistive circuit design) and some control problems, while exhibiting moderate performance on photonic design problems. We also show in many practical cases there exist globally optimal designs whose design parameters are maximized or minimized at each point in the domain, i.e., that there is a discrete globally optimal structure.

    View details for DOI 10.1038/s41598-021-92451-1

    View details for PubMedID 34155295

  • Dirty Pixels: Towards End-to-end Image Processing and Perception ACM TRANSACTIONS ON GRAPHICS Diamond, S., Sitzmann, V., Julca-Aguilar, F., Boyd, S., Wetzstein, G., Heide, F. 2021; 40 (3)

    View details for DOI 10.1145/3446918

    View details for Web of Science ID 000695551400004

  • Extracting a low-dimensional predictable time series OPTIMIZATION AND ENGINEERING Dong, Y., Qin, S., Boyd, S. P. 2021

    View details for DOI 10.1007/s11081-021-09643-x

    View details for Web of Science ID 000655571500001

  • Fitting Laplacian regularized stratified Gaussian models OPTIMIZATION AND ENGINEERING Tuck, J., Boyd, S. 2021

    View details for DOI 10.1007/s11081-021-09611-5

    View details for Web of Science ID 000633757100001

  • Tax-Aware Portfolio Construction via Convex Optimization JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Moehle, N., Kochenderfer, M. J., Boyd, S., Ang, A. 2021

    View details for DOI 10.1007/s10957-021-01823-0

    View details for Web of Science ID 000621695700002

  • Optimal representative sample weighting STATISTICS AND COMPUTING Barratt, S., Angeris, G., Boyd, S. 2021; 31 (2)

    View details for DOI 10.1007/s11222-021-10001-1

    View details for Web of Science ID 000622716900001

  • Heuristic methods and performance bounds for photonic design OPTICS EXPRESS Angeris, G., Vuckovic, J., Boyd, S. 2021; 29 (2): 2827–54

    View details for DOI 10.1364/OE.415052

    View details for Web of Science ID 000609227300184

  • Eigen-stratified models OPTIMIZATION AND ENGINEERING Tuck, J., Boyd, S. 2021

    View details for DOI 10.1007/s11081-020-09592-x

    View details for Web of Science ID 000605507300002

  • Minimum-Distortion Embedding FOUNDATIONS AND TRENDS IN MACHINE LEARNING Agrawal, A., Ali, A., Boyd, S. 2021; 14 (3): 211-378

    View details for DOI 10.1561/2200000090

    View details for Web of Science ID 000695538200001

  • A Distributed Method for Fitting Laplacian Regularized Stratified Models JOURNAL OF MACHINE LEARNING RESEARCH Tuck, J., Barratt, S., Boyd, S. 2021; 22

    View details for Web of Science ID 000656358900001

  • Sample Efficient Reinforcement Learning with REINFORCE Zhang, J., Kim, J., O'Donoghue, B., Boyd, S., Assoc Advancement Artificial Intelligence ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2021: 10887-10895

    View details for Web of Science ID 000681269802065

  • CVXR: An R Package for Disciplined Convex Optimization JOURNAL OF STATISTICAL SOFTWARE Fu, A., Narasimhan, B., Boyd, S. 2020; 94 (14)

    View details for DOI 10.18637/jss.v094.i14

    View details for Web of Science ID 000571010700001

  • Bounds for Scattering from Absorptionless Electromagnetic Structures PHYSICAL REVIEW APPLIED Trivedi, R., Angeris, G., Su, L., Boyd, S., Fan, S., Vuckovic, J. 2020; 14 (1)

    View details for DOI 10.1103/PhysRevApplied.14.014025

    View details for Web of Science ID 000615674000003

  • Automatic repair of convex optimization problems OPTIMIZATION AND ENGINEERING Barratt, S., Angeris, G., Boyd, S. 2020

    View details for DOI 10.1007/s11081-020-09508-9

    View details for Web of Science ID 000535100000001

  • Least squares auto-tuning ENGINEERING OPTIMIZATION Barratt, S. T., Boyd, S. P. 2020

    View details for DOI 10.1080/0305215X.2020.1754406

    View details for Web of Science ID 000532206800001

  • SWIFTCORE: a tool for the context-specific reconstruction of genome-scale metabolic networks. BMC bioinformatics Tefagh, M., Boyd, S. P. 2020; 21 (1): 140

    Abstract

    BACKGROUND: High-throughput omics technologies have enabled the comprehensive reconstructions of genome-scale metabolic networks for many organisms. However, only a subset of reactions is active in each cell which differs from tissue to tissue or from patient to patient. Reconstructing a subnetwork of the generic metabolic network from a provided set of context-specific active reactions is a demanding computational task.RESULTS: We propose SWIFTCC and SWIFTCORE as effective methods for flux consistency checking and the context-specific reconstruction of genome-scale metabolic networks which consistently outperform the previous approaches.CONCLUSIONS: We have derived an approximate greedy algorithm which efficiently scales to increasingly large metabolic networks. SWIFTCORE is freely available for non-commercial use in the GitHub repository at https://mtefagh.github.io/swiftcore/.

    View details for DOI 10.1186/s12859-020-3440-y

    View details for PubMedID 32293238

  • Minimizing a sum of clipped convex functions OPTIMIZATION LETTERS Barratt, S., Angeris, G., Boyd, S. 2020

    View details for DOI 10.1007/s11590-020-01565-4

    View details for Web of Science ID 000521663800002

  • Disciplined quasiconvex programming OPTIMIZATION LETTERS Agrawal, A., Boyd, S. 2020

    View details for DOI 10.1007/s11590-020-01561-8

    View details for Web of Science ID 000517724900001

  • Network optimization for unified packet and circuit switched networks OPTIMIZATION AND ENGINEERING Yin, P., Diamond, S., Lin, B., Boyd, S. 2020; 21 (1): 159–80

    View details for DOI 10.1007/s11081-019-09439-0

    View details for Web of Science ID 000516560400007

  • OSQP: an operator splitting solver for quadratic programs MATHEMATICAL PROGRAMMING COMPUTATION Stellato, B., Banjac, G., Goulart, P., Bemporad, A., Boyd, S. 2020

    View details for DOI 10.1007/s12532-020-00179-2

    View details for Web of Science ID 000517229100002

  • ON THE CONVERGENCE OF MIRROR DESCENT BEYOND STOCHASTIC CONVEX PROGRAMMING SIAM JOURNAL ON OPTIMIZATION Zhou, Z., Mertikopoulos, P., Bambos, N., Boyd, S. P., Glynn, P. W. 2020; 30 (1): 687–716

    View details for DOI 10.1137/17M1134925

    View details for Web of Science ID 000546998300026

  • ANDERSON ACCELERATED DOUGLAS-RACHFORD SPLITTING SIAM JOURNAL ON SCIENTIFIC COMPUTING Fu, A., Zhang, J., Boyd, S. 2020; 42 (6): A3560–A3583

    View details for DOI 10.1137/19M1290097

    View details for Web of Science ID 000600650400012

  • GLOBALLY CONVERGENT TYPE-I ANDERSON ACCELERATION FOR NONSMOOTH FIXED-POINT ITERATIONS SIAM JOURNAL ON OPTIMIZATION Zhang, J., O'Donoghue, B., Boyd, S. 2020; 30 (4): 3170–97

    View details for DOI 10.1137/18M1232772

    View details for Web of Science ID 000600651900018

  • A simple effective heuristic for embedded mixed-integer quadratic programming INTERNATIONAL JOURNAL OF CONTROL Takapoui, R., Moehle, N., Boyd, S., Bemporad, A. 2020; 93 (1): 2–12

    View details for DOI 10.1080/00207179.2017.1316016

    View details for Web of Science ID 000576172600003

  • VARIABLE METRIC PROXIMAL GRADIENT METHOD WITH DIAGONAL BARZILAI-BORWEIN STEPSIZE Park, Y., Dhar, S., Boyd, S., Shah, M., IEEE IEEE. 2020: 3597–3601

    View details for Web of Science ID 000615970403169

  • Fitting a Kalman Smoother to Data Barratt, S. T., Boyd, S. P., IEEE IEEE. 2020: 1526–31

    View details for Web of Science ID 000618079801084

  • Optimal Operation of a Plug-in Hybrid Vehicle with Battery Thermal and Degradation Model Kim, J., Park, Y., Fox, J. D., Boy, S. P., Dally, W., IEEE IEEE. 2020: 3083–90

    View details for Web of Science ID 000618079803006

  • Solution refinement at regular points of conic problems COMPUTATIONAL OPTIMIZATION AND APPLICATIONS Busseti, E., Moursi, W. M., Boyd, S. 2019; 74 (3): 627–43

    View details for DOI 10.1007/s10589-019-00122-9

    View details for Web of Science ID 000495854800002

  • Multi-period portfolio selection with drawdown control Nystrup, P., Boyd, S., Lindstrom, E., Madsen, H. SPRINGER. 2019: 245–71

    View details for DOI 10.1007/s10479-018-2947-3

    View details for Web of Science ID 000490903300011

  • Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Banjac, G., Goulart, P., Stellato, B., Boyd, S. 2019; 183 (2): 490–519

    View details for DOI 10.1007/s10957-019-01575-y

    View details for Web of Science ID 000483695300006

  • A Distributed Method for Optimal Capacity Reservation JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Moehle, N., Shen, X., Luo, Z., Boyd, S. 2019; 182 (3): 1130–49

    View details for DOI 10.1007/s10957-019-01528-5

    View details for Web of Science ID 000475949900014

  • Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace From Position Data IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS Barratt, S. T., Kochenderfer, M. J., Boyd, S. P. 2019; 20 (9): 3536–45

    View details for DOI 10.1109/TITS.2018.2877572

    View details for Web of Science ID 000484207200029

  • Greedy Gaussian segmentation of multivariate time series ADVANCES IN DATA ANALYSIS AND CLASSIFICATION Hallac, D., Nystrup, P., Boyd, S. 2019; 13 (3): 727–51

    View details for DOI 10.1007/s11634-018-0335-0

    View details for Web of Science ID 000483573200008

  • Disciplined geometric programming OPTIMIZATION LETTERS Agrawal, A., Diamond, S., Boyd, S. 2019; 13 (5): 961–76

    View details for DOI 10.1007/s11590-019-01422-z

    View details for Web of Science ID 000469798700001

  • Real-Time Radiation Treatment Planning with Optimality Guarantees via Cluster and Bound Methods INFORMS JOURNAL ON COMPUTING Ungun, B., Xing, L., Boyd, S. 2019; 31 (3): 544–58

    View details for DOI 10.1287/ijoc.2018.0841

    View details for Web of Science ID 000478965300010

  • Computational Bounds for Photonic Design ACS PHOTONICS Angeris, G., Vuckovic, J., Boyd, S. P. 2019; 6 (5): 1232–39

    View details for DOI 10.1021/acsphotonics.9b00154

    View details for Web of Science ID 000468367600021

  • Quantitative flux coupling analysis JOURNAL OF MATHEMATICAL BIOLOGY Tefagh, M., Boyd, S. P. 2019; 78 (5): 1459–84

    View details for DOI 10.1007/s00285-018-1316-9

    View details for Web of Science ID 000463866000009

  • A convex optimization approach to radiation treatment planning with dose constraints OPTIMIZATION AND ENGINEERING Fu, A., Ungun, B., Xing, L., Boyd, S. 2019; 20 (1): 277–300

    View details for DOI 10.1007/s11081-018-9409-2

    View details for Web of Science ID 000457786900010

  • A convex optimization approach to radiation treatment planning with dose constraints. Optimization and engineering Fu, A., Ungun, B., Xing, L., Boyd, S. 2019; 20 (1): 277-300

    Abstract

    We present a method for handling dose constraints as part of a convex programming framework for inverse treatment planning. Our method uniformly handles mean dose, maximum dose, minimum dose, and dose-volume (i.e., percentile) constraints as part of a convex formulation. Since dose-volume constraints are non-convex, we replace them with a convex restriction. This restriction is, by definition, conservative; to mitigate its impact on the clinical objectives, we develop a two-pass planning algorithm that allows each dose-volume constraint to be met exactly on a second pass by the solver if its corresponding restriction is feasible on the first pass. In another variant, we add slack variables to each dose constraint to prevent the problem from becoming infeasible when the user specifies an incompatible set of constraints or when the constraints are made infeasible by our restriction. Finally, we introduce ConRad, a Python-embedded open-source software package for convex radiation treatment planning. ConRad implements the methods described above and allows users to construct and plan cases through a simple interface.

    View details for DOI 10.1007/s11081-018-9409-2

    View details for PubMedID 37990749

    View details for PubMedCentralID PMC10662894

  • Distributed Majorization-Minimization for Laplacian Regularized Problems IEEE-CAA JOURNAL OF AUTOMATICA SINICA Tuck, J., Hallac, D., Boyd, S. 2019; 6 (1): 45–52

    View details for DOI 10.1109/JAS.2019.1911321

    View details for Web of Science ID 000455705900003

  • Differentiable Convex Optimization Layers Agrawal, A., Amos, B., Barratt, S., Boyd, S., Diamond, S., Kolter, J., Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019

    View details for Web of Science ID 000535866901022

  • Quantitative flux coupling analysis. Journal of mathematical biology Tefagh, M., Boyd, S. P. 2018

    Abstract

    Flux coupling analysis (FCA) aims to describe the functional dependencies among reactions in a metabolic network. Currently studied coupling relations are qualitative in the sense that they identify pairs of reactions for which the activity of one reaction necessitates the activity of the other one, but without giving any numerical bounds relating the possible activity rates. The potential applications of FCA are heavily investigated, however apart from some trivial cases there is no clue of what bottleneck in the metabolic network causes each dependency. In this article, we introduce a quantitative approach to the same flux coupling problem named quantitative flux coupling analysis (QFCA). It generalizes the current concepts as we show that all the qualitative information provided by FCA is readily available in the quantitative flux coupling equations of QFCA, without the need for any additional analysis. Moreover, we design a simple algorithm to efficiently identify these flux coupling equations which scales up to the genome-scale metabolic networks with thousands of reactions and metabolites in an effective way. Furthermore, this framework enables us to quantify the "strength" of the flux coupling relations. We also provide different biologically meaningful interpretations, including one which gives an intuitive certificate of precisely which metabolites in the network enforce each flux coupling relation. Eventually, we conclude by suggesting the probable application of QFCA to the metabolic gap-filling problem, which we only begin to address here and is left for future research to further investigate.

    View details for PubMedID 30535964

  • Fitting jump models AUTOMATICA Bemporad, A., Breschi, V., Piga, D., Boyd, S. P. 2018; 96: 11–21

    View details for DOI 10.1016/j.automatica.2018.06.022

    View details for Web of Science ID 000444659500002

  • End-to-end Optimization of Optics and Image Processing for Achromatic Extended Depth of Field and Super-resolution Imaging ACM TRANSACTIONS ON GRAPHICS Sitzmann, V., Diamond, S., Peng, Y., Dun, X., Boyd, S., Heidrich, W., Heide, F., Wetzstein, G. 2018; 37 (4)

    View details for DOI 10.1145/3197517.3201333

    View details for Web of Science ID 000448185000075

  • A semidefinite programming method for integer convex quadratic minimization OPTIMIZATION LETTERS Park, J., Boyd, S. 2018; 12 (3): 499–518

    View details for DOI 10.1007/s11590-017-1132-y

    View details for Web of Science ID 000429677700006

  • Saturating Splines and Feature Selection JOURNAL OF MACHINE LEARNING RESEARCH Boyd, N., Hastie, T., Boyd, S., Recht, B., Jordan, M. 2018; 18

    View details for Web of Science ID 000435454900001

  • A general system for heuristic minimization of convex functions over non-convex sets OPTIMIZATION METHODS & SOFTWARE Diamond, S., Takapoui, R., Boyd, S. 2018; 33 (1): 165-193

    View details for DOI 10.1080/10556788.2017.1304548

    View details for Web of Science ID 000429363200008

  • Prediction error methods in learning jump ARMAX models Breschi, V., Bemporad, A., Piga, D., Boyd, S., IEEE IEEE. 2018: 2247–52

    View details for Web of Science ID 000458114802018

  • Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization Banjac, G., Goulart, P., Stellato, B., Boyd, S., IEEE IEEE. 2018: 340

    View details for Web of Science ID 000454605000071

  • OSQP: An Operator Splitting Solver for Quadratic Programs Stellato, B., Banjac, G., Goulart, P., Bemporad, A., Boyd, S., IEEE IEEE. 2018: 339

    View details for Web of Science ID 000454605000070

  • Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares Boyd, S., Vandenberghe, L. Cambridge University Press. 2018

    View details for DOI 10.1017/9781108583664

  • Saturating Splines and Feature Selection. Journal of machine learning research : JMLR Boyd, N. n., Hastie, T. n., Boyd, S. n., Recht, B. n., Jordan, M. I. 2018; 18

    Abstract

    We extend the adaptive regression spline model by incorporating saturation, the natural requirement that a function extend as a constant outside a certain range. We fit saturating splines to data via a convex optimization problem over a space of measures, which we solve using an efficient algorithm based on the conditional gradient method. Unlike many existing approaches, our algorithm solves the original infinite-dimensional (for splines of degree at least two) optimization problem without pre-specified knot locations. We then adapt our algorithm to fit generalized additive models with saturating splines as coordinate functions and show that the saturation requirement allows our model to simultaneously perform feature selection and nonlinear function fitting. Finally, we briefly sketch how the method can be extended to higher order splines and to different requirements on the extension outside the data range.

    View details for PubMedID 31007630

  • Embedded Mixed-Integer Quadratic Optimization Using the OSQP Solver Stellato, B., Naik, V. V., Bemporad, A., Goulart, P., Boyd, S., IEEE IEEE. 2018: 1536–41

    View details for Web of Science ID 000467725301090

  • Dynamic Resource Allocation for Energy Efficient Transmission in Digital Subscriber Lines IEEE TRANSACTIONS ON SIGNAL PROCESSING Zhang, N., Yao, Z., Liu, Y., Boyd, S. P., Luo, Z. 2017; 65 (16): 4353-4366

    View details for DOI 10.1109/TSP.2017.2711513

    View details for Web of Science ID 000404286900015

  • Network Inference via the Time-Varying Graphical Lasso. KDD : proceedings. International Conference on Knowledge Discovery & Data Mining Hallac, D., Park, Y., Boyd, S., Leskovec, J. 2017; 2017: 205–13

    Abstract

    Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL), a method of inferring time-varying networks from raw time series data. We cast the problem in terms of estimating a sparse time-varying inverse covariance matrix, which reveals a dynamic network of interdependencies between the entities. Since dynamic network inference is a computationally expensive task, we derive a scalable message-passing algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in an efficient way. We also discuss several extensions, including a streaming algorithm to update the model and incorporate new observations in real time. Finally, we evaluate our TVGL algorithm on both real and synthetic datasets, obtaining interpretable results and outperforming state-of-the-art baselines in terms of both accuracy and scalability.

    View details for PubMedID 29770256

  • Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. KDD : proceedings. International Conference on Knowledge Discovery & Data Mining Hallac, D., Vare, S., Boyd, S., Leskovec, J. 2017; 2017: 215–23

    Abstract

    Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios.

    View details for PubMedID 29770257

  • Stochastic Matrix-Free Equilibration JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Diamond, S., Boyd, S. 2017; 172 (2): 436-454

    View details for DOI 10.1007/s10957-016-0990-2

    View details for Web of Science ID 000394266600005

  • Linear Convergence and Metric Selection for Douglas-Rachford Splitting and ADMM IEEE TRANSACTIONS ON AUTOMATIC CONTROL Giselsson, P., Boyd, S. 2017; 62 (2): 532-544

    View details for DOI 10.1109/TAC.2016.2564160

    View details for Web of Science ID 000395510600002

  • SnapVX: A Network-Based Convex Optimization Solver JOURNAL OF MACHINE LEARNING RESEARCH Hallac, D., Wong, C., Diamond, S., Sharang, A., Sosic, R., Boyd, S., Leskovec, J. 2017; 18

    View details for Web of Science ID 000397018200001

  • Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data Hallac, D., Vare, S., Boyd, S., Leskovec, J., ACM ASSOC COMPUTING MACHINERY. 2017: 215-223

    View details for DOI 10.1145/3097983.3098060

    View details for Web of Science ID 000455787300036

  • Network Inference via the Time-Varying Graphical Lasso Hallac, D., Park, Y., Boyd, S., Leskovec, J., ACM ASSOC COMPUTING MACHINERY. 2017: 205-213

    View details for DOI 10.1145/3097983.3098037

    View details for Web of Science ID 000455787300035

  • Stochastic Mirror Descent in Variationally Coherent Optimization Problems Zhou, Z., Mertikopoulos, P., Bambos, N., Boyd, S., Glynn, P., Guyon, Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2017

    View details for Web of Science ID 000452649407013

  • Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields. Proceedings of machine learning research Park, Y. n., Hallac, D. n., Boyd, S. n., Leskovec, J. n. 2017; 54: 1302–10

    Abstract

    Markov random fields (MRFs) are a useful tool for modeling relationships present in large and high-dimensional data. Often, this data comes from various sources and can have diverse distributions, for example a combination of numerical, binary, and categorical variables. Here, we define the pairwise exponential Markov random field (PE-MRF), an approach capable of modeling exponential family distributions in heterogeneous domains. We develop a scalable method of learning the graphical structure across the variables by solving a regularized approximated maximum likelihood problem. Specifically, we first derive a tractable upper bound on the log-partition function. We then use this upper bound to derive the group graphical lasso, a generalization of the classic graphical lasso problem to heterogeneous domains. To solve this problem, we develop a fast algorithm based on the alternating direction method of multipliers (ADMM). We also prove that our estimator is sparsistent, with guaranteed recovery of the true underlying graphical structure, and that it has a polynomially faster runtime than the current state-of-the-art method for learning such distributions. Experiments on synthetic and real-world examples demonstrate that our approach is both efficient and accurate at uncovering the structure of heterogeneous data.

    View details for PubMedID 30931433

  • Disciplined Multi-Convex Programming Shen, X., Diamond, S., Udell, M., Gu, Y., Boyd, S., IEEE IEEE. 2017: 895–900

    View details for Web of Science ID 000427082203091

  • Dynamic Energy Management with Scenario-Based Robust MPC Wytock, M., Moehle, N., Boyd, S., IEEE IEEE. 2017: 2042–47

    View details for Web of Science ID 000427033302017

  • Embedded Code Generation Using the OSQP Solver Banjac, G., Stellato, B., Moehle, N., Goulart, P., Bemporad, A., Boyd, S., IEEE IEEE. 2017

    View details for Web of Science ID 000424696901140

  • SnapVX: A Network-Based Convex Optimization Solver. Journal of machine learning research : JMLR Hallac, D., Wong, C., Diamond, S., Sharang, A., Sosic, R., Boyd, S., Leskovec, J. 2017; 18 (1): 110–14

    Abstract

    SnapVX is a high-performance solver for convex optimization problems defined on networks. For problems of this form, SnapVX provides a fast and scalable solution with guaranteed global convergence. It combines the capabilities of two open source software packages: Snap.py and CVXPY. Snap.py is a large scale graph processing library, and CVXPY provides a general modeling framework for small-scale subproblems. SnapVX offers a customizable yet easy-to-use Python interface with "out-of-the-box" functionality. Based on the Alternating Direction Method of Multipliers (ADMM), it is able to efficiently store, analyze, parallelize, and solve large optimization problems from a variety of different applications. Documentation, examples, and more can be found on the SnapVX website at http://snap.stanford.edu/snapvx.

    View details for PubMedID 29599649

  • Antagonistic control SYSTEMS & CONTROL LETTERS Lipp, T., Boyd, S. 2016; 98: 44-48

    View details for DOI 10.1016/j.sysconle.2016.10.002

    View details for Web of Science ID 000390499500007

  • Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions With Individualized Rotational Arc Trajectory Dong, P., Ungun, B., Boyd, S., Locke, C., Bush, K., Xing, L. ELSEVIER SCIENCE INC. 2016: S228

    View details for DOI 10.1016/j.ijrobp.2016.06.567

    View details for Web of Science ID 000387655805155

  • Optimization of rotational arc station parameter optimized radiation therapy. Medical physics Dong, P., Ungun, B., Boyd, S., Xing, L. 2016; 43 (9): 4973-?

    Abstract

    To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites.The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU.Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case.The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.

    View details for DOI 10.1118/1.4960000

    View details for PubMedID 27587028

    View details for PubMedCentralID PMC4975754

  • Risk-Constrained Kelly Gambling JOURNAL OF INVESTING Busseti, E., Ryu, E. K., Boyd, S. 2016; 25 (3): 118-134

    View details for DOI 10.3905/joi.2016.25.3.118

    View details for Web of Science ID 000410586000013

  • Variations and extension of the convex-concave procedure OPTIMIZATION AND ENGINEERING Lipp, T., Boyd, S. 2016; 17 (2): 263-287

    View details for DOI 10.1007/s11081-015-9294-x

    View details for Web of Science ID 000378411000001

  • Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS O'Donoghue, B., Chu, E., Parikh, N., Boyd, S. 2016; 169 (3): 1042-1068

    View details for DOI 10.1007/s10957-016-0892-3

    View details for Web of Science ID 000376293800016

  • Bounding duality gap for separable problems with linear constraints COMPUTATIONAL OPTIMIZATION AND APPLICATIONS Udell, M., Boyd, S. 2016; 64 (2): 355-378

    View details for DOI 10.1007/s10589-015-9819-4

    View details for Web of Science ID 000376872900002

  • MIMO PID tuning via iterated LMI restriction INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Boyd, S., Hast, M., Astrom, K. J. 2016; 26 (8): 1718-1731

    View details for DOI 10.1002/rnc.3376

    View details for Web of Science ID 000374004500009

  • CVXPY: A Python-Embedded Modeling Language for Convex Optimization. Journal of machine learning research : JMLR Diamond, S., Boyd, S. 2016; 17

    Abstract

    CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples.

    View details for PubMedID 27375369

  • A PRIMER ON MONOTONE OPERATOR METHODS SURVEY APPLIED AND COMPUTATIONAL MATHEMATICS Ryu, E. K., Boyd, S. 2016; 15 (1): 3-43

    View details for Web of Science ID 000371447300001

  • Introduction FOUNDATIONS AND TRENDS IN MACHINE LEARNING Udell, M., Horn, C., Zadeh, R., Boyd, S. 2016; 9 (1): 2-+

    View details for DOI 10.1561/2200000055

    View details for Web of Science ID 000383972700001

  • CVXPY: A Python-Embedded Modeling Language for Convex Optimization JOURNAL OF MACHINE LEARNING RESEARCH Diamond, S., Boyd, S. 2016; 17

    View details for Web of Science ID 000391526800001

  • Maximum Torque-per-Current Control of Induction Motors via Semidefinite Programming Moehle, N., Boyd, S., IEEE IEEE. 2016: 1920-1925

    View details for Web of Science ID 000400048102017

  • Line Search for Averaged Operator Iteration Giselsson, P., Falt, M., Boyd, S., IEEE IEEE. 2016: 1015-1022

    View details for Web of Science ID 000400048101032

  • Disciplined Convex-Concave Programming Shen, X., Diamond, S., Gu, Y., Boyd, S., IEEE IEEE. 2016: 1009-1014

    View details for Web of Science ID 000400048101031

  • A New Architecture for Optimization Modeling Frameworks Wytock, M., Diamond, S., Heide, F., Boyd, S., IEEE IEEE. 2016: 36-44

    View details for DOI 10.1109/PyHPC.2016.5

    View details for Web of Science ID 000401923200005

  • Optimal Resource Allocation for Energy Efficient Transmission in DSL Zhang, N., Yao, Z., Liu, Y., Boyd, S., Luo, Z., IEEE IEEE. 2016

    View details for Web of Science ID 000401963303124

  • Matrix-Free Convex Optimization Modeling OPTIMIZATION AND ITS APPLICATIONS IN CONTROL AND DATA SCIENCES: IN HONOR OF BORIS T. POLYAK'S 80TH BIRTHDAY Diamond, S., Boyd, S., Goldengorin, B. 2016; 115: 221-264

    View details for DOI 10.1007/978-3-319-42056-1_7

    View details for Web of Science ID 000412415400008

  • A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JOURNAL OF MACHINE LEARNING RESEARCH Su, W., Boyd, S., Candes, E. J. 2016; 17

    View details for Web of Science ID 000391664200001

  • Metric selection in fast dual forward-backward splitting AUTOMATICA Giselsson, P., Boyd, S. 2015; 62: 1-10

    View details for DOI 10.1016/j.automatica.2015.09.010

    View details for Web of Science ID 000366233700001

  • A perspective-based convex relaxation for switched-affine optimal control SYSTEMS & CONTROL LETTERS Moehle, N., Boyd, S. 2015; 86: 34-40

    View details for DOI 10.1016/j.sysconle.2015.09.002

    View details for Web of Science ID 000366342100005

  • Extensions of Gauss Quadrature Via Linear Programming FOUNDATIONS OF COMPUTATIONAL MATHEMATICS Ryu, E. K., Boyd, S. P. 2015; 15 (4): 953-971

    View details for DOI 10.1007/s10208-014-9197-9

    View details for Web of Science ID 000358262500004

  • Network Lasso: Clustering and Optimization in Large Graphs. KDD : proceedings. International Conference on Knowledge Discovery & Data Mining Hallac, D., Leskovec, J., Boyd, S. 2015; 2015: 387-396

    Abstract

    Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. Therefore, there is a need for simple, scalable algorithms that can solve many common optimization problems. In this paper, we introduce the network lasso, a generalization of the group lasso to a network setting that allows for simultaneous clustering and optimization on graphs. We develop an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in a distributed and scalable manner, which allows for guaranteed global convergence even on large graphs. We also examine a non-convex extension of this approach. We then demonstrate that many types of problems can be expressed in our framework. We focus on three in particular - binary classification, predicting housing prices, and event detection in time series data - comparing the network lasso to baseline approaches and showing that it is both a fast and accurate method of solving large optimization problems.

    View details for PubMedID 27398260

  • Approximate dynamic programming via iterated Bellman inequalities INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Wang, Y., O'Donoghue, B., Boyd, S. 2015; 25 (10): 1472-1496

    View details for DOI 10.1002/rnc.3152

    View details for Web of Science ID 000354641300004

  • Optimal current waveforms for brushless permanent magnet motors INTERNATIONAL JOURNAL OF CONTROL Moehle, N., Boyd, S. 2015; 88 (7): 1389-1399

    View details for DOI 10.1080/00207179.2015.1012558

    View details for Web of Science ID 000355733700007

  • Model predictive control for wind power gradients WIND ENERGY Hovgaard, T. G., Boyd, S., Jorgensen, J. B. 2015; 18 (6): 991-1006

    View details for DOI 10.1002/we.1742

    View details for Web of Science ID 000353355900003

  • TH-AB-BRB-02: Enabling Web-Based Treatment Planning Using a State-Of-The-Art Convex Optimization Solver. Medical physics Ungun, B., Folkerts, M., Bush, K., Boyd, S., Xing, L. 2015; 42 (6): 3704-?

    Abstract

    To develop an ultra-fast web-based inverse planning framework for VMAT/IMRT. To achieve high speed, we investigate the use of a simple convex formulation of the inverse treatment planning problem that takes advantage of recent developments in the field of distributed optimization.A Monte Carlo (MC) dose calculation algorithm was used to calculate the dose matrix (268228 voxels x 360 beams, 96M non-zeros) for a 360-aperture, 4-arc VMAT plan taken from the clinic. We wrote the objective for the inverse treatment planning problem as a sum of convex (piecewise-linear) penalties on the dose at each voxel in the planning volume. This convex voxel-separable formulation allowed us to apply a new, open-source, CPU- and GPU-capable optimization solver (http://foges.github.io/pogs/) to calculate our solutions of optimal beam intensities. In each planning session, after performing one full optimization we accelerated subsequent runs by "warm-starting": for run k, the optimal solution from run k-1 was used as an initial guess. We implemented the treatment planning application as a Python web server running on a standard g2-2xlarge GPU node on Amazon EC2.Our method formed optimal treatment plans in 5-15 seconds. Warm-start times ranged from 100ms-8s (mean 3s) while sweeping out a 5-log range of tradeoffs between target coverage and OAR sparing in 1000 total optimizations. Satisfactory plans were reached in 1-10 iterations of the optimization, with total planning time <10 minutes. Dosimetric characteristics such as the DVH curves showed that the resultant plans were comparable or superior to the clinically delivered plan.This work demonstrates the feasibility of high-quality, low-latency treatment planning using a convex problem formulation and GPU- based convex solver, making it practical to manipulate treatment objectives and view DVH curves and dose-wash views in nearly real-time in a web application. Funding support for this work is provided by the Stanford Bio-X Bowes Graduate Fellowship and NIH Grant 5R01CA176553.

    View details for DOI 10.1118/1.4926133

    View details for PubMedID 26129432

  • Linear Models Based on Noisy Data and the Frisch Scheme. SIAM review. Society for Industrial and Applied Mathematics Ning, L., Georgiou, T. T., Tannenbaum, A., Boyd, S. P. 2015; 57 (2): 167-197

    Abstract

    We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is that measurement errors in each variable are independent. This basic formulation has its roots in the work of Charles Spearman in 1904 and of Ragnar Frisch in the 1930s. Various topics such as errors-in-variables, factor analysis, and instrumental variables all refer to alternative viewpoints on this problem and on ways to account for the anticipated way that noise enters the data. In the present paper we begin by describing certain fundamental contributions by the founders of the field and provide alternative modern proofs to certain key results. We then go on to consider a modern viewpoint and novel numerical techniques to the problem. The central theme is expressed by the Frisch-Kalman dictum, which calls for identifying a noise contribution that allows a maximal number of simultaneous linear relations among the noise-free variables-a rank minimization problem. In the years since Frisch's original formulation, there have been several insights, including trace minimization as a convenient heuristic to replace rank minimization. We discuss convex relaxations and theoretical bounds on the rank that, when met, provide guarantees for global optimality. A complementary point of view to this minimum-rank dictum is presented in which models are sought leading to a uniformly optimal quadratic estimation error for the error-free variables. Points of contact between these formalisms are discussed, and alternative regularization schemes are presented.

    View details for DOI 10.1137/130921179

    View details for PubMedID 27168672

    View details for PubMedCentralID PMC4856315

  • Linear Models Based on Noisy Data and the Frisch Scheme SIAM REVIEW Ning, L., Georgiou, T. T., Tannenbaum, A., Boyd, S. P. 2015; 57 (2): 167-197

    Abstract

    We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is that measurement errors in each variable are independent. This basic formulation has its roots in the work of Charles Spearman in 1904 and of Ragnar Frisch in the 1930s. Various topics such as errors-in-variables, factor analysis, and instrumental variables all refer to alternative viewpoints on this problem and on ways to account for the anticipated way that noise enters the data. In the present paper we begin by describing certain fundamental contributions by the founders of the field and provide alternative modern proofs to certain key results. We then go on to consider a modern viewpoint and novel numerical techniques to the problem. The central theme is expressed by the Frisch-Kalman dictum, which calls for identifying a noise contribution that allows a maximal number of simultaneous linear relations among the noise-free variables-a rank minimization problem. In the years since Frisch's original formulation, there have been several insights, including trace minimization as a convenient heuristic to replace rank minimization. We discuss convex relaxations and theoretical bounds on the rank that, when met, provide guarantees for global optimality. A complementary point of view to this minimum-rank dictum is presented in which models are sought leading to a uniformly optimal quadratic estimation error for the error-free variables. Points of contact between these formalisms are discussed, and alternative regularization schemes are presented.

    View details for DOI 10.1137/130921179

    View details for Web of Science ID 000354985600001

    View details for PubMedCentralID PMC4856315

  • Network Lasso: Clustering and Optimization in Large Graphs Hallac, D., Leskovec, J., Boyd, S., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2015: 387-396

    View details for DOI 10.1145/2783258.2783313

    View details for Web of Science ID 000485312900043

  • Non-Parametric Regression Modeling for Stochastic Optimization of Power Grid Load Forecast Shenoy, S., Gorinevsky, D., Boyd, S., IEEE IEEE. 2015: 1010-1015

    View details for Web of Science ID 000370259201015

  • Convex Optimization with Abstract Linear Operators Diamond, S., Boyd, S., IEEE IEEE. 2015: 675-683

    View details for DOI 10.1109/ICCV.2015.84

    View details for Web of Science ID 000380414100076

  • Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization Ali, A., Kolter, J., Diamond, S., Boyd, S., Meila, M., Heskes, T. AUAI PRESS. 2015: 62-71

    View details for Web of Science ID 000493121100007

  • Optimizing Beam Angles and Aperture Shapes Simultaneously for Station Parameter Optimized Radiation Therapy (SPORT) Zarepisheh, M., Ye, Y., Boyd, S., Li, R., Xing, L. ELSEVIER SCIENCE INC. 2014: S108-S109

    View details for DOI 10.1016/j.ijrobp.2014.05.526

    View details for Web of Science ID 000342331400246

  • Minimum-time speed optimisation over a fixed path INTERNATIONAL JOURNAL OF CONTROL Lipp, T., Boyd, S. 2014; 87 (6): 1297-1311

    View details for DOI 10.1080/00207179.2013.875224

    View details for Web of Science ID 000333996000017

  • Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT) Zarepisheh, M., Ye, Y., Boyd, S., Li, R., Xing, L. WILEY. 2014

    View details for DOI 10.1118/1.4888627

    View details for Web of Science ID 000436933200003

  • Optimal Crowd-Powered Rating and Filtering Algorithms PROCEEDINGS OF THE VLDB ENDOWMENT Parameswaran, A., Boyd, S., Garcia-Molina, H., Gupta, A., Polyzotis, N., Widom, J. 2014; 7 (9): 685-696

    View details for DOI 10.14778/2732939.2732942

    View details for Web of Science ID 000219810200004

  • Block splitting for distributed optimization MATHEMATICAL PROGRAMMING COMPUTATION Parikh, N., Boyd, S. 2014; 6 (1): 77-102

    View details for DOI 10.1007/s12532-013-0061-8

    View details for Web of Science ID 000219348600004

  • Quadratic approximate dynamic programming for input-affine systems INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Keshavarz, A., Boyd, S. 2014; 24 (3): 432-449

    View details for DOI 10.1002/rnc.2894

    View details for Web of Science ID 000329439900003

  • Dynamic network energy management via proximal message passing Foundations and Trends in Optimization, Original version posted 4/1/12. Kraning, M., Chu, E., Lavaei, J., Boyd, S. 2014; 2 (1): 70-122
  • Diagonal Scaling in Douglas-Rachford Splitting and ADMM Giselsson, P., Boyd, S., IEEE IEEE. 2014: 5033-5039

    View details for Web of Science ID 000370073805033

  • Preconditioning in Fast Dual Gradient Methods Giselsson, P., Boyd, S., IEEE IEEE. 2014: 5040-5045

    View details for Web of Science ID 000370073805034

  • Monotonicity and Restart in Fast Gradient Methods Giselsson, P., Boyd, S., IEEE IEEE. 2014: 5058-5063

    View details for Web of Science ID 000370073805037

  • Decentralized control of plug-in electric vehicles under driving uncertainty Vaya, M., Andersson, G., Boyd, S., IEEE IEEE. 2014

    View details for Web of Science ID 000393467600259

  • A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights Su, W., Boyd, S., Candes, E. J., Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D., Weinberger, K. Q. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2014

    View details for Web of Science ID 000452647100101

  • Security Constrained Optimal Power Flow via Proximal Message Passing Clemson-University Power Systems Conference (PSC) Chakrabarti, S., Kraning, M., Chu, E., Baldick, R., Boyd, S. IEEE. 2014

    View details for Web of Science ID 000352000600040

  • Proximal algorithms Foundations and Trends in Optimization Boyd, S., Parikh, N. 2014; 3 (1): 123-231
  • Performance bounds and suboptimal policies for multi-period investment Foundations and Trends in Optimization, Original version Boyd, S., Mueller, M., O'Donoghue, B., Wang, Y. 2014; 1 (1): 1-69
  • A Splitting Method for Optimal Control IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY O'Donoghue, B., Stathopoulos, G., Boyd, S. 2013; 21 (6): 2432-2442

    View details for DOI 10.1109/TCST.2012.2231960

    View details for Web of Science ID 000326105800040

  • Nonconvex model predictive control for commercial refrigeration INTERNATIONAL JOURNAL OF CONTROL Hovgaard, T. G., Boyd, S., Larsen, L. F., Jorgensen, J. B. 2013; 86 (8): 1349-1366

    View details for DOI 10.1080/00207179.2012.742207

    View details for Web of Science ID 000322807900004

  • Risk group detection and survival function estimation for interval coded survival methods NEUROCOMPUTING Van Belle, V., Neven, P., Harvey, V., Van Huffel, S., Suykens, J. A., Boyd, S. 2013; 112: 200-210

    View details for DOI 10.1016/j.neucom.2012.12.049

    View details for Web of Science ID 000319952500019

  • A distributed algorithm for fitting generalized additive models OPTIMIZATION AND ENGINEERING Chu, E., Keshavarz, A., Boyd, S. 2013; 14 (2): 213-224

    View details for DOI 10.1007/s11081-013-9215-9

    View details for Web of Science ID 000319884600001

  • A primal-dual operator splitting method for conic optimization Working Draft. Chu, E., O'Donoghue, B., Parikh, N., Boyd, S. 2013
  • Code Generation for Embedded Second-Order Cone Programming European Control Conference (ECC) Chu, E., Parikh, N., Domahidi, A., Boyd, S. IEEE. 2013: 1547–1552

    View details for Web of Science ID 000332509701153

  • Cost Optimal Operation of Thermal Energy Storage System with Real-Time Prices 2nd International Conference on Control, Automation and Information Sciences (ICCAIS) Kashima, T., Boyd, S. P. IEEE. 2013

    View details for Web of Science ID 000345828200041

  • PID Design by Convex-Concave Optimization European Control Conference (ECC) Hast, M., Astrom, K. J., Bernhardsson, B., Boyd, S. IEEE. 2013: 4460–4465

    View details for Web of Science ID 000332509704144

  • ECOS: An SOCP Solver for Embedded Systems European Control Conference (ECC) Domahidi, A., Chu, E., Boyd, S. IEEE. 2013: 3077–3082

    View details for Web of Science ID 000332509703078

  • ECOS: An SOCP solver for embedded systems Domahidi, A., Chu, E., Boyd, S. 2013
  • Cost optimal operation of thermal energy storage system with real-time prices Kashima, T., Boyd, S. 2013
  • Code generation for embedded second-order cone programming Chu, E., Parikh, N., Domahidi, A., Boyd, S. 2013
  • Iterated approximate value functions O'Donoghue, B., Wang, Y., Boyd, S. 2013
  • MPC for Wind Power Gradients - Utilizing Forecasts, Rotor Inertia, and Central Energy Storage European Control Conference (ECC) Hovgaard, T. G., Larsen, L. F., Jorgensen, J. B., Boyd, S. IEEE. 2013: 4071–4076

    View details for Web of Science ID 000332509704079

  • Model predictive control for wind power gradients Hovgaard, T., Boyd, S., Jørgensen, J. 2013
  • Block splitting for distributed optimization Mathematical Programming Computation, Shorter preliminary version appeared as NIPS workshop paper. Parikh, N., Boyd, S. 2013
  • PID design by convex-concave optimization Hast, M., Astrom, K., Bernhardsson, B., Boyd, S. 2013
  • Robust optimization of adiabatic tapers for coupling to slow-light photonic-crystal waveguides OPTICS EXPRESS Oskooi, A., Mutapcic, A., Noda, S., Joannopoulos, J. D., Boyd, S. P., Johnson, S. G. 2012; 20 (19): 21558-21575

    Abstract

    We investigate the design of taper structures for coupling to slow-light modes of various photonic-crystal waveguides while taking into account parameter uncertainties inherent in practical fabrication. Our short-length (11 periods) robust tapers designed for ? = 1.55?m and a slow-light group velocity of c/34 have a total loss of < 20 dB even in the presence of nanometer-scale surface roughness, which outperform the corresponding non-robust designs by an order of magnitude. We discover a posteriori that the robust designs have smooth profiles that can be parameterized by a few-term (intrinsically smooth) sine series which helps the optimization to further boost the performance slightly. We ground these numerical results in an analytical foundation by deriving the scaling relationships between taper length, taper smoothness, and group velocity with the help of an exact equivalence with Fourier analysis.

    View details for Web of Science ID 000308865600094

    View details for PubMedID 23037275

  • Dose optimization with first-order total-variation minimization for dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) MEDICAL PHYSICS Kim, H., Li, R., Lee, R., Goldstein, T., Boyd, S., Candes, E., Xing, L. 2012; 39 (7): 4316-4327

    Abstract

    A new treatment scheme coined as dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) has recently been proposed to bridge the gap between IMRT and VMAT. By increasing the angular sampling of radiation beams while eliminating dispensable segments of the incident fields, DASSIM-RT is capable of providing improved conformity in dose distributions while maintaining high delivery efficiency. The fact that DASSIM-RT utilizes a large number of incident beams represents a major computational challenge for the clinical applications of this powerful treatment scheme. The purpose of this work is to provide a practical solution to the DASSIM-RT inverse planning problem.The inverse planning problem is formulated as a fluence-map optimization problem with total-variation (TV) minimization. A newly released L1-solver, template for first-order conic solver (TFOCS), was adopted in this work. TFOCS achieves faster convergence with less memory usage as compared with conventional quadratic programming (QP) for the TV form through the effective use of conic forms, dual-variable updates, and optimal first-order approaches. As such, it is tailored to specifically address the computational challenges of large-scale optimization in DASSIM-RT inverse planning. Two clinical cases (a prostate and a head and neck case) are used to evaluate the effectiveness and efficiency of the proposed planning technique. DASSIM-RT plans with 15 and 30 beams are compared with conventional IMRT plans with 7 beams in terms of plan quality and delivery efficiency, which are quantified by conformation number (CN), the total number of segments and modulation index, respectively. For optimization efficiency, the QP-based approach was compared with the proposed algorithm for the DASSIM-RT plans with 15 beams for both cases.Plan quality improves with an increasing number of incident beams, while the total number of segments is maintained to be about the same in both cases. For the prostate patient, the conformation number to the target was 0.7509, 0.7565, and 0.7611 with 80 segments for IMRT with 7 beams, and DASSIM-RT with 15 and 30 beams, respectively. For the head and neck (HN) patient with a complicated target shape, conformation numbers of the three treatment plans were 0.7554, 0.7758, and 0.7819 with 75 segments for all beam configurations. With respect to the dose sparing to the critical structures, the organs such as the femoral heads in the prostate case and the brainstem and spinal cord in the HN case were better protected with DASSIM-RT. For both cases, the delivery efficiency has been greatly improved as the beam angular sampling increases with the similar or better conformal dose distribution. Compared with conventional quadratic programming approaches, first-order TFOCS-based optimization achieves far faster convergence and smaller memory requirements in DASSIM-RT.The new optimization algorithm TFOCS provides a practical and timely solution to the DASSIM-RT or other inverse planning problem requiring large memory space. The new treatment scheme is shown to outperform conventional IMRT in terms of dose conformity to both the targetand the critical structures, while maintaining high delivery efficiency.

    View details for DOI 10.1118/1.4729717

    View details for Web of Science ID 000306893000029

    View details for PubMedID 22830765

  • Smoothed state estimates under abrupt changes using sum-of-norms regularization AUTOMATICA Ohlsson, H., Gustafsson, F., Ljung, L., Boyd, S. 2012; 48 (4): 595-605

    View details for DOI 10.1016/j.automatica.2011.08.063

    View details for Web of Science ID 000302766400002

  • A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology PLOS ONE Van Belle, V. M., Van Calster, B., Timmerman, D., Bourne, T., Bottomley, C., Valentin, L., Neven, P., Van Huffel, S., Suykens, J. A., Boyd, S. 2012; 7 (3)

    Abstract

    Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data.

    View details for DOI 10.1371/journal.pone.0034312

    View details for Web of Science ID 000304523400072

    View details for PubMedID 22479598

    View details for PubMedCentralID PMC3315538

  • CVXGEN: a code generator for embedded convex optimization OPTIMIZATION AND ENGINEERING Mattingley, J., Boyd, S. 2012; 13 (1): 1-27

    View details for DOI 10.1007/s11081-011-9176-9

    View details for Web of Science ID 000299176900001

  • Moving Horizon Estimation for Staged QP Problems 51st IEEE Annual Conference on Decision and Control (CDC) Chu, E., Keshavarz, A., Gorinevsky, D., Boyd, S. IEEE. 2012: 3177–3182

    View details for Web of Science ID 000327200403087

  • Accuracy at the top Boyd, S., Cortes, C., Mohri, M., Radovanovic, A. 2012
  • Quadratic approximate dynamic programming for input-affine systems International Journal of Robust and Nonlinear Control, published on-line Keshavarz, A., Boyd, S. 2012
  • An ADMM algorithm for a class of total variation regularized estimation problems Wahlberg, B., Boyd, S., Annergren, M., Wang, Y. 2012
  • Performance bounds and suboptimal policies for linear stochastic control via LMIs INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Wang, Y., Boyd, S. 2011; 21 (14): 1710-1728

    View details for DOI 10.1002/rnc.1665

    View details for Web of Science ID 000294256000007

  • Fast Evaluation of Quadratic Control-Lyapunov Policy IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY Wang, Y., Boyd, S. 2011; 19 (4): 939-946

    View details for DOI 10.1109/TCST.2010.2056371

    View details for Web of Science ID 000291808700021

  • Receding Horizon Control AUTOMATIC GENERATION OF HIGH-SPEED SOLVERS IEEE CONTROL SYSTEMS MAGAZINE Mattingley, J., Wang, Y., Boyd, S. 2011; 31 (3): 52-65

    View details for DOI 10.1109/MCS.2011.940571

    View details for Web of Science ID 000290630500009

  • Inferring stable genetic networks from steady-state data AUTOMATICA Zavlanos, M. M., Julius, A. A., Boyd, S. P., Pappas, G. J. 2011; 47 (6): 1113-1122

    View details for DOI 10.1016/j.automatica.2011.02.006

    View details for Web of Science ID 000291456100004

  • Inverse design of a three-dimensional nanophotonic resonator OPTICS EXPRESS Lu, J., Boyd, S., Vuckovic, J. 2011; 19 (11): 10563-10570

    Abstract

    The inverse design of a three-dimensional nanophotonic resonator is presented. The design methodology is computationally fast (10 minutes on a standard desktop workstation) and utilizes a 2.5-dimensional approximation of the full three-dimensional structure. As an example, we employ the proposed method to design a resonator which exhibits a mode volume of 0.32(λ/n)3 and a quality factor of 7063.

    View details for Web of Science ID 000290852800050

    View details for PubMedID 21643310

  • Self-Tuning for Maximized Lifetime Energy-Efficiency in the Presence of Circuit Aging IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS Mintarno, E., Skaf, J., Zheng, R., Velamala, J. B., Cao, Y., Boyd, S., Dutton, R. W., Mitra, S. 2011; 30 (5): 760-773

    View details for DOI 10.1109/TCAD.2010.2100531

    View details for Web of Science ID 000289843900010

  • Controller coefficient truncation using Lyapunov performance certificate INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Skaf, J., Boyd, S. P. 2011; 21 (1): 55-78

    View details for DOI 10.1002/rnc.1577

    View details for Web of Science ID 000285936300004

  • Imputing a Convex Objective Function IEEE International Symposium on Intelligent Control (ISIC)/IEEE Multi-Conference on Systems and Control (MSC) Keshavarz, A., Wang, Y., Boyd, S. IEEE. 2011: 613–619

    View details for Web of Science ID 000297500400015

  • Load Reduction of Wind Turbines Using Receding Horizon Control IEEE International Conference on Control Applications (CCA) Soltani, M., Wisniewski, R., Brath, P., Boyd, S. IEEE. 2011: 852–857

    View details for Web of Science ID 000297216500091

  • Min-max approximate dynamic programming O'Donoghue, B., Wang, Y., Boyd, S. 2011
  • Scalable statistical monitoring of fleet data Chu, E., Gorinevsky, D., Boyd, S. 2011
  • Operation and configuration of a storage portfolio via convex optimization Kraning, M., Wang, Y., Akuiyibo, E., Boyd, S. 2011
  • Block splitting for large-scale distributed learning Parikh, N., Boyd, S. 2011
  • Receding horizon control: Automatic generation of high-speed solvers IEEE Control Systems Magazine Mattingley, J., Wang, Y., Boyd, S. 2011; 3 (31): 52–65
  • Distributed optimization and statistical learning via the alternating direction method of multipliers Foundations and Trends in Machine Learning Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J. 2011; 1 (3): 1–122
  • Load reduction of wind turbines using receding horizon control Soltani, M., Wisniewski, R., Brath, P., Boyd, S. 2011
  • Wind Turbine Pitch Optimization IEEE International Conference on Control Applications (CCA) Biegel, B., Juelsgaard, M., Kraning, M., Boyd, S., Stoustrup, J. IEEE. 2011: 1327–1334

    View details for Web of Science ID 000297216500151

  • Shrinking-horizon dynamic programming INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Skaf, J., Boyd, S., Zeevi, A. 2010; 20 (17): 1993-2002

    View details for DOI 10.1002/rnc.1566

    View details for Web of Science ID 000284215900007

  • A unified framework for 3D radiation therapy and IMRT planning: plan optimization in the beamlet domain by constraining or regularizing the fluence map variations PHYSICS IN MEDICINE AND BIOLOGY Meng, B., Zhu, L., Widrow, B., Boyd, S., Xing, L. 2010; 55 (22): N521-N531

    Abstract

    The purpose of this work is to demonstrate that physical constraints on fluence gradients in 3D radiation therapy (RT) planning can be incorporated into beamlet optimization explicitly by direct constraint on the spatial variation of the fluence maps or implicitly by using total-variation regularization (TVR). The former method forces the fluence to vary in accordance with the known form of a wedged field and latter encourages the fluence to take the known form of the wedged field by requiring the derivatives of the fluence maps to be piece-wise constant. The performances of the proposed methods are evaluated by using a brain cancer case and a head and neck case. It is found that both approaches are capable of providing clinically sensible 3D RT solutions with monotonically varying fluence maps. For currently available 3D RT delivery schemes based on the use of customized physical or dynamic wedges, constrained optimization seems to be more useful because the optimized fields are directly deliverable. Working in the beamlet domain provides a natural way to model the spatial variation of the beam fluence. The proposed methods take advantage of the fact that 3D RT is a special form of intensity-modulated radiation therapy (IMRT) and finds the optimal plan by searching for fields with a certain type of spatial variation. The approach provides a unified framework for 3D CRT and IMRT plan optimization.

    View details for DOI 10.1088/0031-9155/55/22/N01

    View details for Web of Science ID 000283789700001

    View details for PubMedID 21030744

  • Design of Affine Controllers via Convex Optimization IEEE TRANSACTIONS ON AUTOMATIC CONTROL Skaf, J., Boyd, S. P. 2010; 55 (11): 2476-2487

    View details for DOI 10.1109/TAC.2010.2046053

    View details for Web of Science ID 000283940800003

  • Compressed sensing based cone-beam computed tomography reconstruction with a first-order method MEDICAL PHYSICS Choi, K., Wang, J., Zhu, L., Suh, T., Boyd, S., Xing, L. 2010; 37 (9): 5113-5125

    Abstract

    This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements.The authors cast the reconstruction as a compressed sensing problem based on l1 norm minimization constrained by statistically weighted least-squares of CBCT projection data. For accurate modeling, the noise characteristics of the CBCT projection data are used to determine the relative importance of each projection measurement. To solve the compressed sensing problem, the authors employ a method minimizing total-variation norm, satisfying a prespecified level of measurement consistency using a first-order method developed by Nesterov.The method converges fast to the optimal solution without excessive memory requirement, thanks to the method of iterative forward and back-projections. The performance of the proposed algorithm is demonstrated through a series of digital and experimental phantom studies. It is found a that high quality CBCT image can be reconstructed from undersampled and potentially noisy projection data by using the proposed method. Both sparse sampling and decreasing x-ray tube current (i.e., noisy projection data) lead to the reduction of radiation dose in CBCT imaging.It is demonstrated that compressed sensing outperforms the traditional algorithm when dealing with sparse, and potentially noisy, CBCT projection views.

    View details for DOI 10.1118/1.3481510

    View details for Web of Science ID 000281906000063

    View details for PubMedID 20964231

    View details for PubMedCentralID PMC2945747

  • Fast Algorithms for Resource Allocation in Wireless Cellular Networks IEEE-ACM TRANSACTIONS ON NETWORKING Madan, R., Boyd, S. P., Lall, S. 2010; 18 (3): 973-984

    View details for DOI 10.1109/TNET.2009.2034850

    View details for Web of Science ID 000278813900023

  • Segmentation of ARX-models using sum-of-norms regularization AUTOMATICA Ohlsson, H., Ljung, L., Boyd, S. 2010; 46 (6): 1107-1111

    View details for DOI 10.1016/j.automatica.2010.03.013

    View details for Web of Science ID 000278675500020

  • Techniques for exploring the suboptimal set OPTIMIZATION AND ENGINEERING Skaf, J., Boyd, S. 2010; 11 (2): 319-337

    View details for DOI 10.1007/s11081-009-9101-7

    View details for Web of Science ID 000277790400006

  • Real-Time Convex Optimization in Signal Processing IEEE SIGNAL PROCESSING MAGAZINE Mattingley, J., Boyd, S. 2010; 27 (3): 50-61

    View details for DOI 10.1109/MSP.2010.936020

    View details for Web of Science ID 000276819100008

  • Mixed linear system estimation and identification SIGNAL PROCESSING Zymnis, A., Boyd, S., Gorinevsky, D. 2010; 90 (3): 966-971

    View details for DOI 10.1016/j.sigpro.2009.09.022

    View details for Web of Science ID 000272433400024

  • Fast Model Predictive Control Using Online Optimization IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY Wang, Y., Boyd, S. 2010; 18 (2): 267-278

    View details for DOI 10.1109/TCST.2009.2017934

    View details for Web of Science ID 000274996100003

  • Compressed Sensing With Quantized Measurements IEEE SIGNAL PROCESSING LETTERS Zymnis, A., Boyd, S., Candes, E. 2010; 17 (2): 149-152

    View details for DOI 10.1109/LSP.2009.2035667

    View details for Web of Science ID 000272046700001

  • Adaptive Modulation in Wireless Networks with Smoothed Flow Utility IEEE Global Telecommunications Conference (GLOBECOM 2010) Akuiyibo, E., Boyd, S., O'Neill, D. IEEE. 2010

    View details for Web of Science ID 000287977405131

  • Optimized Self-Tuning for Circuit Aging Mintarno, E., Skaf, J., Zheng, R., Velamala, J., Cao, Y., Boyd, S., Dutton, R. W., Mitra, S., IEEE IEEE. 2010: 586–91

    View details for Web of Science ID 000397468600109

  • Detecting aircraft performance anomalies from cruise flight data Chu, E., Gorinesky, D., Boyd, S. 2010
  • Automatic code generation for real-time convex optimization Convex Optimization in Signal Processing and Communications Mattingley, J., Boyd, S. edited by Eldar, Y., Palomar, D. Cambridge University Press. 2010: 1–41
  • State Smoothing by Sum-of-Norms Regularization 49th IEEE Conference on Decision and Control (CDC) Ohlsson, H., Gustafsson, F., Ljung, L., Boyd, S. IEEE. 2010: 2880–2885

    View details for Web of Science ID 000295049103054

  • Trajectory Generation Using Sum-of-Norms Regularization 49th IEEE Conference on Decision and Control (CDC) Ohlsson, H., Gustafsson, F., Ljung, L., Boyd, S. IEEE. 2010: 540–545

    View details for Web of Science ID 000295049100089

  • Adaptive Modulation with Smoothed Flow Utility EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING Akuiyibo, E., Boyd, S. 2010

    View details for DOI 10.1155/2010/815213

    View details for Web of Science ID 000285616900001

  • Optimizing Adaptive Modulation in Wireless Networks via Multi-Period Network Utility Maximization 2010 IEEE International Conference on Communications O'Neill, D., Akuiyibo, E., Boyd, S., Goldsmith, A. J. IEEE. 2010

    View details for Web of Science ID 000290335602179

  • Nonlinear Q-Design for Convex Stochastic Control IEEE TRANSACTIONS ON AUTOMATIC CONTROL Skaf, J., Boyd, S. 2009; 54 (10): 2426-2430

    View details for DOI 10.1109/TAC.2009.2029300

    View details for Web of Science ID 000270950200015

  • Processor Speed Control With Thermal Constraints IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS Mutapcic, A., Boyd, S., Murali, S., Atienza, D., De Micheli, G., Gupta, R. 2009; 56 (9): 1994-2008

    View details for DOI 10.1109/TCSI.2008.2011589

    View details for Web of Science ID 000269684700001

  • l(1) Trend Filtering SIAM REVIEW Kim, S., Koh, K., Boyd, S., Gorinevsky, D. 2009; 51 (2): 339-360

    View details for DOI 10.1137/070690274

    View details for Web of Science ID 000266289500003

  • Relaxed maximum a posteriori fault identification SIGNAL PROCESSING Zymnis, A., Boyd, S., Gorinevsky, D. 2009; 89 (6): 989-999

    View details for DOI 10.1016/j.sigpro.2008.11.014

    View details for Web of Science ID 000264941900004

  • Genetic network identification using convex programming IET SYSTEMS BIOLOGY Julius, A., Zavlanos, M., Boyd, S., Pappas, G. J. 2009; 3 (3): 155-166

    Abstract

    Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expression levels of the genes are typically measured as mRNA concentration in micro-array experiments. In a so-called genetic perturbation experiment, small perturbations are applied to equilibrium states and the resulting changes in expression activity are measured. One of the most important problems in systems biology is to use these data to identify the interaction pattern between genes in a regulatory network, especially in a large scale network. The authors develop a novel algorithm for identifying the smallest genetic network that explains genetic perturbation experimental data. By construction, our identification algorithm is able to incorporate and respect a priori knowledge known about the network structure. A priori biological knowledge is typically qualitative, encoding whether one gene affects another gene or not, or whether the effect is positive or negative. The method is based on a convex programming relaxation of the combinatorially hard problem of L(0) minimisation. The authors apply the proposed method to the identification of a subnetwork of the SOS pathway in Escherichia coli, the segmentation polarity network in Drosophila melanogaster, and an artificial network for measuring the performance of the method.

    View details for DOI 10.1049/iet-syb.2008.0130

    View details for Web of Science ID 000267060600003

    View details for PubMedID 19449976

  • Regular Analog/RF Integrated Circuits Design Using Optimization With Recourse Including Ellipsoidal Uncertainty IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS Xu, Y., Hsiung, K., Li, X., Pileggi, L. T., Boyd, S. P. 2009; 28 (5): 623-637

    View details for DOI 10.1109/TCAD.2009.2013996

    View details for Web of Science ID 000265486900002

  • Performance bounds for linear stochastic control SYSTEMS & CONTROL LETTERS Wang, Y., Boyd, S. 2009; 58 (3): 178-182

    View details for DOI 10.1016/j.sysconle.2008.10.004

    View details for Web of Science ID 000263494300003

  • Optimal Estimation of Deterioration From Diagnostic Image Sequence IEEE TRANSACTIONS ON SIGNAL PROCESSING Gorinevsky, D., Kim, S., Beard, S., Boyd, S., Gordon, G. 2009; 57 (3): 1030-1043

    View details for DOI 10.1109/TSP.2008.2009896

    View details for Web of Science ID 000263431900018

  • Analysis and Synthesis of State-Feedback Controllers With Timing Jitter IEEE TRANSACTIONS ON AUTOMATIC CONTROL Skaf, J., Boyd, S. 2009; 54 (3): 652-657

    View details for DOI 10.1109/TAC.2008.2010998

    View details for Web of Science ID 000264397200027

  • Convex piecewise-linear fitting OPTIMIZATION AND ENGINEERING Magnani, A., Boyd, S. P. 2009; 10 (1): 1-17

    View details for DOI 10.1007/s11081-008-9045-3

    View details for Web of Science ID 000263388400001

  • Sensor Selection via Convex Optimization IEEE TRANSACTIONS ON SIGNAL PROCESSING Joshi, S., Boyd, S. 2009; 57 (2): 451-462

    View details for DOI 10.1109/TSP.2008.2007095

    View details for Web of Science ID 000263161500004

  • FASTEST MIXING MARKOV CHAIN ON GRAPHS WITH SYMMETRIES SIAM JOURNAL ON OPTIMIZATION Boyd, S., Diaconis, P., Parrilo, P., Xiao, L. 2009; 20 (2): 792-819

    View details for DOI 10.1137/070689413

    View details for Web of Science ID 000268859300011

  • Mixed Linear System Estimation and Identification Joint 48th IEEE Conference on Decision and Control (CDC) / 28th Chinese Control Conference (CCC) Zymnis, A., Boyd, S., Gorinevsky, D. IEEE. 2009: 1501–1506

    View details for Web of Science ID 000336893601163

  • Subspaces that minimize the condition number of a matrix Rejecta Mathematica Joshi, S., Boyd, S. 2009; 1 (1): 4-9
  • Optimized self-tuning for circuit aging Mintarno, E., Skaf, J., Zheng, R., Velamela, J., Cao, Y., Boyd, S. 2009
  • Estimation of Faults in DC Electrical Power System American Control Conference 2009 Gorinevsky, D., Boyd, S., Poll, S. IEEE. 2009: 4334–4339

    View details for Web of Science ID 000270044902059

  • Distributed Large Scale Network Utility Maximization IEEE International Symposium on Information Theory (ISIT 2009) Bickson, D., Tock, Y., Zymnis, A., Boyd, S. P., Dolev, D. IEEE. 2009: 829–833

    View details for Web of Science ID 000280141400169

  • Cutting-set methods for robust convex optimization with pessimizing oracles OPTIMIZATION METHODS & SOFTWARE Mutapcic, A., Boyd, S. 2009; 24 (3): 381-406

    View details for DOI 10.1080/10556780802712889

    View details for Web of Science ID 000265975500005

  • An efficient method for large-scale slack allocation ENGINEERING OPTIMIZATION Joshi, S., Boyd, S. 2009; 41 (12): 1163-1176

    View details for DOI 10.1080/03052150902971682

    View details for Web of Science ID 000208108300005

  • Wireless NUM: Rate and Reliability Tradeoffs in Random Environments IEEE Wireless Communications and Networking Conference O'Neill, D., Thian, B. S., Goldsmith, A., Boyd, S. IEEE. 2009: 444–449

    View details for Web of Science ID 000272057700080

  • Robust design of slow-light tapers in periodic waveguides ENGINEERING OPTIMIZATION Mutapcic, A., Boyd, S., Farjadpour, A., Johnson, S. G., Avniel, Y. 2009; 41 (4): 365-384

    View details for DOI 10.1080/03052150802576797

    View details for Web of Science ID 000264741600005

  • Enhancing Sparsity by Reweighted l(1) Minimization 4th IEEE International Symposium on Biomedical Imaging Candes, E. J., Wakin, M. B., Boyd, S. P. SPRINGER. 2008: 877–905

    View details for DOI 10.1007/s00041-008-9045-x

    View details for Web of Science ID 000261411300013

  • An Efficient Method for Large-Scale Gate Sizing IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS Joshi, S., Boyd, S. 2008; 55 (9): 2760-2773

    View details for DOI 10.1109/TCSI.2008.920087

    View details for Web of Science ID 000260863700030

  • Filter design with low complexity coefficients IEEE TRANSACTIONS ON SIGNAL PROCESSING Skaf, J., Boyd, S. P. 2008; 56 (7): 3162-3169

    View details for DOI 10.1109/TSP.2008.919386

    View details for Web of Science ID 000257195900010

  • Tractable approximate robust geometric programming OPTIMIZATION AND ENGINEERING Hsiung, K., Kim, S., Boyd, S. 2008; 9 (2): 95-118

    View details for DOI 10.1007/s11081-007-9025-z

    View details for Web of Science ID 000254251500001

  • Compensation of multimode fiber dispersion using adaptive optics via convex optimization JOURNAL OF LIGHTWAVE TECHNOLOGY Panicker, R. A., Kahn, J. M., Boyd, S. P. 2008; 26 (9-12): 1295-1303

    View details for DOI 10.1109/JLT.2008.917324

    View details for Web of Science ID 000256971400030

  • Robust beamforming via worst-case SINR maximization IEEE TRANSACTIONS ON SIGNAL PROCESSING Kim, S., Magnani, A., Mutapcic, A., Boyd, S. P., Luo, Z. 2008; 56 (4): 1539-1547

    View details for DOI 10.1109/TSP.2007.911498

    View details for Web of Science ID 000254118300020

  • Minimizing effective resistance of a graph SIAM REVIEW Ghosh, A., Boyd, S., Saberi, A. 2008; 50 (1): 37-66

    View details for DOI 10.1137/050645452

    View details for Web of Science ID 000253646600004

  • Design of low-bandwidth spatially distributed feedback IEEE TRANSACTIONS ON AUTOMATIC CONTROL Gorinevsky, D., Boyd, S., Stein, G. 2008; 53 (1): 257-272

    View details for DOI 10.1109/TAC.2007.914950

    View details for Web of Science ID 000254022000002

  • FURTHER RELAXATIONS OF THE SEMIDEFINITE PROGRAMMING APPROACH TO SENSOR NETWORK LOCALIZATION SIAM JOURNAL ON OPTIMIZATION Wang, Z., Zheng, S., Ye, Y., Boyd, S. 2008; 19 (2): 655-673

    View details for DOI 10.1137/060669395

    View details for Web of Science ID 000260849600008

  • Graph Implementations for Nonsmooth Convex Programs RECENT ADVANCES IN LEARNING AND CONTROL Grant, M. C., Boyd, S. P., Blondel, V. D., Boyd, S. P., Kimura, H. 2008; 371: 95-110

    View details for DOI 10.1007/978-1-84800-155-8_7

    View details for Web of Science ID 000267163500007

  • Graph implementations for nonsmooth convex programs Recent Advances in Learning and Control (tribute to M. Vidyasagar), Lecture Notes in Control and Information Sciences Grant, M., Boyd, S. edited by Boyd, S., Kimura, H. 2008: 95–110
  • Two-fund separation under model mis-specification Working paper Kim, S., -J., Boyd, S. 2008
  • Temperature control of high-performance multi-core platforms using convex optimization Design, Automation and Test in Europe Conference and Exhibition (DATE 08) Murali, S., Mutapcic, A., Atienza, D., Gupta, R., Boyd, S., Benini, L., De Micheli, G. IEEE. 2008: 108–113

    View details for Web of Science ID 000257940700021

  • Identification of stable genetic networks using convex programming American Control Conference 2008 Zavlanos, M. M., Julius, A. A., Boyd, S. P., Pappas, G. J. IEEE. 2008: 2755–2760

    View details for Web of Science ID 000259261502020

  • Learning the kernel via convex optimization 33rd IEEE International Conference on Acoustics, Speech and Signal Processing Kim, S., Zymnis, A., Magnani, A., Koh, K., Boyd, S. IEEE. 2008: 1997–2000

    View details for Web of Science ID 000257456701161

  • Mixed State Estimation for a Linear Gaussian Markov Model 47th IEEE Conference on Decision and Control Zymnis, A., Boyd, S., Gorinevsky, D. IEEE. 2008: 3219–3226

    View details for Web of Science ID 000307311603058

  • Cross-Layer Design with Adaptive Modulation: Delay, Rate, and Energy Tradeoffs IEEE Global Telecommunications Conference (GLOBECOM 08) O'Neill, D., Goldsmith, A. J., Boyd, S. IEEE. 2008

    View details for DOI 10.1109/GLOCOM.2008.ECP.818

    View details for Web of Science ID 000287978004070

  • Optimizing adaptive modulation in wireless networks via utility maximization IEEE International Conference on Communications (ICC 2008) O'Neill, D., Goldsmith, A. J., Boyd, S. IEEE. 2008: 3372–3377

    View details for Web of Science ID 000259505002124

  • A MINIMAX THEOREM WITH APPLICATIONS TO MACHINE LEARNING, SIGNAL PROCESSING, AND FINANCE SIAM JOURNAL ON OPTIMIZATION Kim, S., Boyd, S. 2008; 19 (3): 1344-1367

    View details for DOI 10.1137/060677586

    View details for Web of Science ID 000263103900017

  • Wireless Network Utility Maximization IEEE Military Communications Conference (MILCOM 2008) O'Neill, D., Goldsmith, A., Boyd, S. IEEE. 2008: 2314–2321

    View details for Web of Science ID 000266709301072

  • Mixed State Estimation for a Linear Gaussian Markov Model 10th International Conference on Control, Automation, Robotics and Vision Zymnis, A., Boyd, S., Gorinevsky, D. IEEE. 2008: 1005–1011

    View details for Web of Science ID 000266716600175

  • Fast computation of optimal contact forces IEEE TRANSACTIONS ON ROBOTICS Boyd, S. P., Wegbreit, B. 2007; 23 (6): 1117-1132

    View details for DOI 10.1109/TRO.2007.910774

    View details for Web of Science ID 000251944100002

  • A heuristic for optimizing stochastic activity networks with applications to statistical digital circuit sizing OPTIMIZATION AND ENGINEERING Kim, S., Boyd, S. P., Yun, S., Patil, D. D., Horowitz, M. A. 2007; 8 (4): 397-430

    View details for DOI 10.1007/s11081-007-9011-5

    View details for Web of Science ID 000249952000003

  • An Interior-Point Method for Large-Scale l(1)-Regularized Least Squares IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING Kim, S., Koh, K., Lustig, M., Boyd, S., Gorinevsky, D. 2007; 1 (4): 606-617

    View details for DOI 10.1109/JSTSP.2007.910971

    View details for Web of Science ID 000265494900008

  • An interior-point method for large-scale l(1)-regularized logistic regression JOURNAL OF MACHINE LEARNING RESEARCH Koh, K., Kim, S., Boyd, S. 2007; 8: 1519-1555

    View details for Web of Science ID 000249353700006

  • Beamforming with uncertain weights IEEE SIGNAL PROCESSING LETTERS Mutapcic, A., Kim, S., Boyd, S. 2007; 14 (5): 348-351

    View details for DOI 10.1109/LSP.2006.888102

    View details for Web of Science ID 000245910100014

  • A tutorial on geometric programming OPTIMIZATION AND ENGINEERING Boyd, S., Kim, S., Vandenberghe, L., Hassibi, A. 2007; 8 (1): 67-127

    View details for DOI 10.1007/s11081-007-9001-7

    View details for Web of Science ID 000247679000004

  • Generalized Chebyshev bounds via semidefinite programming SIAM REVIEW Vandenberghe, L., Boyd, S., Comanor, K. 2007; 49 (1): 52-64

    View details for DOI 10.1137/S003614450440543

    View details for Web of Science ID 000244514000005

  • Portfolio optimization with linear and fixed transaction costs ANNALS OF OPERATIONS RESEARCH Sousa Lobo, M., Fazel, M., Boyd, S. 2007; 152: 341-365

    View details for DOI 10.1007/s10479-006-0145-1

    View details for Web of Science ID 000245750900015

  • Temperature-aware processor frequency assignment for MPSoCs using convex optimization Murali, S., Mutapcic, A., Atienza, D., Gupta, R., Boyd, S., De Micheli, G. 2007
  • Dynamic network utility maximization with delivery contracts Trichakis, N., Zymnis, A., Boyd, S. 2007
  • Robust efficient frontier analysis with a separable uncertainty model Working paper Kim, S., -J., Boyd, S. 2007
  • Distributed estimation via dual decomposition Samar, S., Boyd, S., Gorinevsky, D. 2007
  • An interior-point method for large-scale network utility maximization Zymnis, A., Trichakis, N., Boyd, S., O'Neill, D. 2007
  • Optimal estimation of accumulating damage trend from a series of SHM images 6th International Workshop on Structural Health Monitoring Gorinevsky, D., Kim, S., Boyd, S., Gordon, G., Beard, S., Chang, F. DESTECH PUBLICATIONS, INC. 2007: 1340–1346

    View details for Web of Science ID 000254290001033

  • An efficient method for compressed sensing IEEE International Conference on Image Processing (ICIP 2007) Kim, S., Koh, K., Lustig, M., Boyd, S. IEEE. 2007: 1245–1248

    View details for Web of Science ID 000253487201071

  • An efficient method for large-scale l(1)-regularized convex loss minimization IEEE Information Theory and Applications Workshop Koh, K., Kim, S., Boyd, S. IEEE. 2007: 221–228

    View details for Web of Science ID 000250812500032

  • Hyperspectral image unmixing via alternating projected subgradients 41st Asilomar Conference on Signals, Systems and Computers Zymnis, A., Kim, S., Skaf, J., Parente, M., Boyd, S. IEEE. 2007: 1164–1168

    View details for Web of Science ID 000257172900224

  • Robust Chebyshev FIR equalization IEEE Global Telecommunications Conference (GLOBECOM 07) Mutapcic, A., Kim, S., Boyd, S. IEEE. 2007: 3074–3079

    View details for Web of Science ID 000257505703003

  • A minimax theorem with applications to machine learning, signal processing, and finance 46th IEEE Conference on Decision and Control Kim, S., Boyd, S. IEEE. 2007: 5180–5187

    View details for Web of Science ID 000255181703022

  • A tractable method for robust downlink beamforming in wireless communications 41st Asilomar Conference on Signals, Systems and Computers Mutapcic, A., Kim, S., Boyd, S. IEEE. 2007: 1224–1228

    View details for Web of Science ID 000257172900236

  • Distributed average consensus with least-mean-square deviation JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING Xiao, L., Boyd, S., Kim, S. 2007; 67 (1): 33-46

    View details for DOI 10.1016/j.jpdc.2006.08.010

    View details for Web of Science ID 000243614700003

  • The fastest mixing Markov process on a graph and a connection to a maximum variance unfolding problem SIAM REVIEW Sun, J., Boyd, S., Xiao, L., Diaconis, P. 2006; 48 (4): 681-699

    View details for DOI 10.1137/S0036144504443821

    View details for Web of Science ID 000242326500002

  • Upper bounds on algebraic connectivity via convex optimization LINEAR ALGEBRA AND ITS APPLICATIONS Ghosh, A., Boyd, S. 2006; 418 (2-3): 693-707

    View details for DOI 10.1016/j.laa.2006.03.006

    View details for Web of Science ID 000241258500024

  • Optimal scaling of a gradient method for distributed resource allocation JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS Xiao, L., Boyd, S. 2006; 129 (3): 469-488

    View details for DOI 10.1007/s10957-006-9080-1

    View details for Web of Science ID 000242828800008

  • Extending scope of robust optimization: Comprehensive robust counterparts of uncertain problems MATHEMATICAL PROGRAMMING Ben-Tal, A., Boyd, S., Nemirovski, A. 2006; 107 (1-2): 63-89

    View details for DOI 10.1007/s10107-005-0679-z

    View details for Web of Science ID 000235808200004

  • Randomized gossip algorithms IEEE TRANSACTIONS ON INFORMATION THEORY Boyd, S., Ghosh, A., Prabhakar, B., Shah, D. 2006; 52 (6): 2508-2530

    View details for DOI 10.1109/TIT.2006.874516

    View details for Web of Science ID 000238319400016

  • Optimization-based design and implementation of multidimensional zero-phase IIR filters IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS Gorinevsky, D., Boyd, S. 2006; 53 (2): 372-383

    View details for DOI 10.1109/TCSI.2005.856048

    View details for Web of Science ID 000235403400015

  • Embedded estimation of fault parameters in an unmanned aerial vehicle IEEE International Conference on Control Applications Samar, S., Gorinevsky, D., Boyd, S. P. IEEE. 2006: 2082–2087

    View details for Web of Science ID 000245233803078

  • A linear programming approach for the worst-case norm of uncertain linear systems subject to disturbances with magnitude and rate bounds 45th IEEE Conference on Decision and Control Khaisongkram, W., Boyd, S., Banjerdpongchai, D. IEEE. 2006: 4399–4404

    View details for Web of Science ID 000252251604102

  • Optimal kernel selection in kernel Fisher discriminant analysis Kim, S., J., Magnani, A., Boyd, S. 2006
  • Pareto optimal linear classification Kim, S., J., Magnani, A., Samar, S., Boyd, S., Lim, J. 2006
  • Disciplined convex programming Global Optimization: From Theory to Implementation, in the book series Nonconvex Optimization and its Applications Grant, M., Boyd, S., Ye, Y. edited by Liberti, L., Maculan, N. 2006: 155–210
  • Convex optimization of graph Laplacian eigenvalues Boyd, S. 2006
  • A duality view of spectral methods for dimensionality reduction Xiao, L., Sun, J., Boyd, S. 2006
  • Design tools for emerging technologies Johnson, S., Avniel, Y., White, J., Boyd, S. 2006
  • A space-time diffusion scheme for peer-to-peer least-squares estimation 5th International Conference on Informational Processing in Sensor Networks Xiao, L., Boyd, S., Lall, S. ASSOC COMPUTING MACHINERY. 2006: 168–176

    View details for Web of Science ID 000238978000022

  • A heuristic method for statistical digital circuit sizing 4th Conference on Design and Process Integration for Microelectronic Manufacturing Boyd, S., Kim, S., Patil, D., Horowitz, M. SPIE-INT SOC OPTICAL ENGINEERING. 2006

    View details for DOI 10.1117/12.657499

    View details for Web of Science ID 000238444200008

  • Fastest mixing Markov chain on a path AMERICAN MATHEMATICAL MONTHLY Boyd, S., Diaconis, P., Sun, J., Xiao, L. 2006; 113 (1): 70-74

    View details for Web of Science ID 000234776200007

  • Growing well-connected graphs 45th IEEE Conference on Decision and Control Ghosh, A., Boyd, S. IEEE. 2006: 6605–6611

    View details for Web of Science ID 000252251600100

  • Array signal processing with robust rejection constraints via second-order cone programming 40th Asilomar Conference on Signals, Systems and Computers Mutapcic, A., Kim, S., Boyd, S. IEEE. 2006: 2267–2270

    View details for Web of Science ID 000246925204079

  • Optimal doping profiles via geometric programming IEEE TRANSACTIONS ON ELECTRON DEVICES Joshi, S., Boyd, S., Dutton, R. W. 2005; 52 (12): 2660-2675

    View details for DOI 10.1109/TED.2005.859649

    View details for Web of Science ID 000233682200019

  • Digital circuit optimization via geometric programming OPERATIONS RESEARCH Boyd, S. P., Kim, S. J., Patil, D. D., Horowitz, M. A. 2005; 53 (6): 899-932

    View details for DOI 10.1287/opre.1050.0254

    View details for Web of Science ID 000234756000002

  • Piecewise-affine state feedback for piecewise-affine slab systems using convex optimization SYSTEMS & CONTROL LETTERS Rodrigues, L., Boyd, S. 2005; 54 (9): 835-853

    View details for DOI 10.1016/j.sysconle.2005.01.002

    View details for Web of Science ID 000230733200002

  • Robust minimum variance beamforming IEEE TRANSACTIONS ON SIGNAL PROCESSING Lorenz, R. G., Boyd, S. R. 2005; 53 (5): 1684-1696

    View details for DOI 10.1109/TSP.2005.845436

    View details for Web of Science ID 000228403500007

  • A new method for design of robust digital circuits 6th International Symposium on Quality Electronic Design Patil, D., Yun, S. H., Kim, S. J., Cheung, A., Horowitz, M., Boyd, S. IEEE COMPUTER SOC. 2005: 676–681

    View details for Web of Science ID 000228486600110

  • Symmetry Analysis of Reversible Markov Chains INTERNET MATHEMATICS Boyd, S., Diaconis, P., Parrilo, P., Xiao, L. 2005; 2 (1): 31-71

    View details for DOI 10.1080/15427951.2005.10129100

    View details for Web of Science ID 000217614400003

  • OPERA: Optimization with ellipsoidal uncertainty for robust analog IC design Xu, Y., Hsiung, K., L., Li, X., Nausieda, I., Boyd, S., Pileggi, L. 2005
  • Robust Fisher discriminant analysis Advances in Neural Information Processing Systems Kim, S., -J., Magnani, A., Boyd, S. 2005; 18: 659-666
  • Mixing times for random walks on geometric random graphs Boyd, S., Ghosh, A., Prabhakar, B., Shah, D. 2005
  • On time-invariant purified-output-based discrete time control echnical report 5/2005, Minerva Optimization Center, Technion, Haifa, Israel. Ben Tal, A., Boyd, S., Nemirovski, A. 2005
  • Geometric programming for circuit optimization Boyd, S., Kim, S., J. 2005
  • Symmetry analysis of reversible Markov chains Internet Mathematics Boyd, S., Diaconis, P., Parrilo, P., Xiao, L. 2005; 1 (2): 31-71
  • Joint optimization of wireless communication and networked control systems European Summer School on Multi-Agent Control Xiao, L., Johansson, M., Hindi, H., Boyd, S., GOLDSMITH, A. SPRINGER-VERLAG BERLIN. 2005: 248–272

    View details for Web of Science ID 000228664100011

  • Gossip algorithms: Design, analysis and applications 24th Annual Joint Conference of the IEEE Computer and Communications Societies Boyd, S., Ghosh, A., Prabhakar, B., Shah, D. IEEE COMPUTER SOC. 2005: 1653–1664

    View details for Web of Science ID 000231441002014

  • Tractable fitting with convex polynomials via sum-of-squares 44th IEEE Conference on Decision Control/European Control Conference (CCD-ECC) Magnani, A., Lall, S., Boyd, S. IEEE. 2005: 1672–1677

    View details for Web of Science ID 000240653701110

  • Power control in lognormal fading wireless channels with uptime probability specifications via robust geometric programming American Control Conference 2005 (ACC) Hsiung, K. L., Kim, S. J., Boyd, S. IEEE. 2005: 3955–3959

    View details for Web of Science ID 000231947705042

  • A scheme for robust distributed sensor fusion based on average consensus 4th International Symposium on Information Processing in Sensor Networks Xiao, L., Boyd, S., Lall, S. IEEE. 2005: 63–70

    View details for Web of Science ID 000230452800009

  • Likelihood bounds for constrained estimation with uncertainty 44th IEEE Conference on Decision Control/European Control Conference (CCD-ECC) Samar, S., Gorinevsky, D., Boyd, S. IEEE. 2005: 5704–5709

    View details for Web of Science ID 000240653705083

  • Least-squares covariance matrix adjustment SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Boyd, S., Xiao, L. 2005; 27 (2): 532-546

    View details for DOI 10.1137/040609902

    View details for Web of Science ID 000233579300013

  • Near-optimal depth-constrained codes IEEE TRANSACTIONS ON INFORMATION THEORY Gupta, P., Prabhakar, B., Boyd, S. 2004; 50 (12): 3294-3298

    View details for DOI 10.1109/TIT.2004.838345

    View details for Web of Science ID 000225363000023

  • Fastest mixing Markov chain on a graph SIAM REVIEW Boyd, S., Diaconis, P., Xiao, L. 2004; 46 (4): 667-689

    View details for DOI 10.1137/s0036144503423264

    View details for Web of Science ID 000225304300006

  • Fast linear iterations for distributed averaging SYSTEMS & CONTROL LETTERS Xiao, L., Boyd, S. 2004; 53 (1): 65-78

    View details for DOI 10.1016/j.sysconle.2004.02.022

    View details for Web of Science ID 000223114900006

  • Simultaneous routing and resource allocation via dual decomposition 4th Asian Control Conference Xiao, L., Johansson, M., Boyd, S. P. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2004: 1136–44

    View details for DOI 10.1109/TCOMM.2004.831346

    View details for Web of Science ID 000222761100017

  • Geometric programming duals of channel capacity and rate distortion IEEE International Symposium on Information Theory Chiang, M., Boyd, S. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2004: 245–58

    View details for DOI 10.1109/TIT.2003.822581

    View details for Web of Science ID 000188949100001

  • Iterative water-filling for Gaussian vector multiple-access channels IEEE International Symposium on Information Theory Yu, W., Rhee, W. J., Boyd, S., Cioffi, J. M. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2004: 145–52

    View details for DOI 10.1109/TIT.2003.821988

    View details for Web of Science ID 000188371800010

  • Designing fast distributed iterations via semidefinite programming Xiao, L., Boyd, S. 2004
  • A decomposition approach to distributed analysis of networked systems Langbort, C., Xiao, L., D'Andrea, R., Boyd, S. 2004
  • Distributed optimization for cooperative agents: Application to formation flight 43rd IEEE Conference on Decision and Control Raffard, R. L., Tomlin, C. J., Boyd, S. P. IEEE. 2004: 2453–2459

    View details for Web of Science ID 000226745602032

  • Convex Optimization Boyd, S., Vandenberghe, L. Cambridge University Press. 2004
  • Convex Optimization Boyd, S., Vandenberghe, L. Cambridge University Press. 2004
  • ORACLE: Optimization with recourse of analog circuits including layout extraction 41st Design Automation Conference Xu, Y., Pileggi, L. T., Boyd, S. R. ASSOC COMPUTING MACHINERY. 2004: 151–154

    View details for Web of Science ID 000223078800035

  • Decomposition approach to distributed analysis of networked systems 43rd IEEE Conference on Decision and Control Langbort, U., Xiao, L., D'Andrea, R., Boyd, S. IEEE. 2004: 3980–3985

    View details for Web of Science ID 000226745603105

  • Rank minimization and applications in system theory American Control Conference Fazel, M., Hindi, H., Boyd, S. IEEE. 2004: 3273–3278

    View details for Web of Science ID 000224688300556

  • Piecewise-affine state feedback using convex optimization American Control Conference Rodrigues, L., Boyd, S. IEEE. 2004: 5164–5169

    View details for Web of Science ID 000224688300877

  • Equalization of modal dispersion in multimode fiber using spatial light modulators IEEE Global Telecommunications Conference (GLOBECOM 04) Alon, E., Stojanovic, V., Kahn, J. M., Boyd, S., Horowitz, M. IEEE. 2004: 1023–1029

    View details for Web of Science ID 000226689900195

  • Analysis and optimization of randomized gossip algorithms 43rd IEEE Conference on Decision and Control Boyd, S., Ghosh, A., Prabhakar, B., Shah, D. IEEE. 2004: 5310–5315

    View details for Web of Science ID 000226745604134

  • Adaptive management of network resources 58th IEEE Vehicular Technology Conference (VTC 2003) ONeill, D. C., Julian, D., Boyd, S. IEEE. 2004: 1929–1933

    View details for Web of Science ID 000221662300391

  • MP-DSM: A distributed cross layer network control protocol IEEE International Conference on Communications (ICC 2004) O'Neill, D. C., Li, Y., Boyd, S. IEEE. 2004: 2102–2106

    View details for Web of Science ID 000223459600409

  • Managing power consumption in networks on chips IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS Simunic, T., Boyd, S. P., Glynn, P. 2004; 12 (1): 96-107

    View details for DOI 10.1109/TVLSI.2003.820533

    View details for Web of Science ID 000188735900007

  • Moving horizon filter for monotonic trends 43rd IEEE Conference on Decision and Control Samar, S., Gorinevsky, D., Boyd, S. IEEE. 2004: 3115–3120

    View details for Web of Science ID 000226745602146

  • Future directions in control in an information-rich world - A summary of the report of the Panel, on Future Directions in Control, Dynamics, and Systems. IEEE CONTROL SYSTEMS MAGAZINE Murray, R. M., Astrom, K. M., Boyd, S. P., Brockett, R. W., Stein, G. 2003; 23 (2): 20-33

    View details for Web of Science ID 000181786000005

  • Joint optimization of communication rates and linear systems IEEE TRANSACTIONS ON AUTOMATIC CONTROL Xiao, L., Johansson, M., Hindi, H., Boyd, S., Goldsmith, A. 2003; 48 (1): 148-153

    View details for DOI 10.1109/TAC.2002.806669

    View details for Web of Science ID 000180424600019

  • Simultaneous routing and resource allocation in CDMA wireless data networks Johansson, M., Xiao, L., Boyd, S. 2003
  • Control in an information rich world in Control in an Information-Rich World, in IEEE Control Systems Magazine Murray, R., Astrom, K., Boyd, S., Brockett, R., Stein, G. 2003; 2 (23): 20-33
  • Worst-case capacity of vector Gaussian channels Vishwanath, S., Boyd, S., Goldsmith, A. 2003
  • Throughput-centric routing algorithm design Towles, B., Dally, W., Boyd, S. 2003
  • Optimization-based tuning of low-bandwidth control in spatially distributed systems Annual American Control Conference (ACC 2003) Gorinevsky, D., Boyd, S., Stein, G. IEEE. 2003: 2658–2663

    View details for Web of Science ID 000186706200451

  • Optimization of phase-locked loop circuits via geometric programming 25th Annual Custom Integrated Circuits Conference Colleran, D. M., Portmann, C., Hassibi, A., Crusius, C., Mohan, S. S., Boyd, S., Lee, T. H., Hershenson, M. D. IEEE. 2003: 377–380

    View details for Web of Science ID 000186714300075

  • Robust minimum variance beamforming 37th Asilomar Conference on Signals, Systems and Computers Lorenz, R. G., Boyd, S. P. IEEE. 2003: 1345–1352

    View details for Web of Science ID 000189498700252

  • Simultaneous routing and power allocation in CDMA wireless data networks IEEE International Conference on Communications (ICC) Johansson, M., Xiao, L., Boyd, S. IEEE. 2003: 51–55

    View details for Web of Science ID 000183802400010

  • Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices Annual American Control Conference (ACC 2003) Fazel, M., Hindi, H., Boyd, S. P. IEEE. 2003: 2156–2162

    View details for Web of Science ID 000186706200365

  • Fast linear iterations for distributed averaging 42nd IEEE Conference on Decision and Control Xiao, L., Boyd, S. IEEE. 2003: 4997–5002

    View details for Web of Science ID 000189434100857

  • Geometric programming dual of channel capacity IEEE International Symposium on Information Theory Chiang, M., Boyd, S. IEEE. 2003: 291–291

    View details for Web of Science ID 000186112600291

  • Computing optimal uncertainty models from frequency domain data 41st IEEE Conference on Decision and Control Hindi, H., Seong, C. Y., Boyd, S. IEEE. 2002: 2898–2905

    View details for Web of Science ID 000181352300520

  • Robust linear programming and optimal control Vandenberghe, L., Boyd, S., Nouralishahi, M. 2002
  • Advances in convex optimization: Theory, algorithms, and applications Boyd, S., Vandenberghe, L. 2002
  • Advances in convex optimization: Interior-point methods, cone programming, and applications Boyd, S., Vandenberghe, L. 2002
  • Convex optimization of output link scheduling and active queue management in QoS constrained packet switches IEEE International Conference on Communications Chiang, M., Chan, B. L., Boyd, S. IEEE. 2002: 2126–2130

    View details for Web of Science ID 000177818300410

  • An ellipsoidal approximation to the Hadamard product of ellipsoids IEEE International Conference on Acoustics, Speech, and Signal Processing Lorenz, R., Boyd, S. IEEE. 2002: 1193–1196

    View details for Web of Science ID 000177510400299

  • Managing power consumption in networks on chips Design, Automation and Test in Europe Conference and Exhibition (DATE 2002) Simunic, T., Boyd, S. IEEE COMPUTER SOC. 2002: 110–116

    View details for Web of Science ID 000176953300017

  • Efficient nonlinear optimizations of queuing systems IEEE Global Telecommunications Conference (GLOBECOM 02) Chiang, M., Sutivong, A., Boyd, S. IEEE. 2002: 2425–2429

    View details for Web of Science ID 000182118500480

  • QoS and fairness constrained convex optimization of resource allocation for wireless cellular and ad hoc networks 21st Annual Joint Conference of the IEEE-Computer-and-Communications-Societies Julian, D., Chiang, M., O'Neill, D., Boyd, S. IEEE. 2002: 477–486

    View details for Web of Science ID 000178147300051

  • Optimal power control in interference-limited fading wireless channels with outage-probability specifications IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS Kandukuri, S., Boyd, S. 2002; 1 (1): 46-55

    View details for Web of Science ID 000182431900005

  • Optimal design of a CMOS op-amp via geometric programming IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS Hershenson, M. D., Boyd, S. P., Lee, T. H. 2001; 20 (1): 1-21

    View details for Web of Science ID 000167206200001

  • Design of robust global power and ground networks Boyd, S., Vandenberghe, L., El Gamal, A., Yun, S. 2001
  • A rank minimization heuristic with application to minimum order system approximation American Control Conference (ACC) Fazel, M., Hindi, H., Boyd, S. P. IEEE. 2001: 4734–4739

    View details for Web of Science ID 000173663300845

  • Resource allocation for QoS provisioning in wireless ad hoc networks IEEE Global Telecommunications Conference (GLOBECOM 01) Chiang, M., ONEILL, D., JULIAN, D., Boyd, S. IEEE. 2001: 2911–2915

    View details for Web of Science ID 000178714800560

  • Optimal allocation of local feedback in multistage amplifiers via geometric programming IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS Dawson, J. L., Boyd, S. P., Hershenson, M. D., Lee, T. H. 2001; 48 (1): 1-11

    View details for Web of Science ID 000166993700001

  • Joint optimization of communication rates and linear systems 40th IEEE Conference on Decision and Control Xiao, L., Johansson, M., Hindi, H., Boyd, S., Goldsmith, A. IEEE. 2001: 2321–2326

    View details for Web of Science ID 000178362200422

  • New approaches speed up optimization of analog designs ELECTRONIC DESIGN Boyd, S. 2000; 48 (20): 62-62

    View details for Web of Science ID 000089763400011

  • Bandwidth extension in CMOS with optimized on-chip inductors IEEE Custom Integrated Circuits Conference Mohan, S. S., Hershenson, M. D., Boyd, S. P., Lee, T. H. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2000: 346–55

    View details for Web of Science ID 000086290700007

  • Optimal allocation of local feedback in multistage amplifiers via geometric programming 43rd IEEE Midwest Symposium on Circuits and Systems Dawson, J. L., Boyd, S. P., Lee, T. H., Hershenson, M. D. IEEE. 2000: 530–533

    View details for Web of Science ID 000172099300122

  • Dynamic emission tomography - regularization and inversion Maeght, J., Noll, D., Boyd, S. 2000
  • Simutaneous rate and power control in multirate CDMA systems Kandukuri, S., Boyd, S. 2000
  • Finding ultimate limits of performance for hybrid electric vehicles Tate, E., Boyd, S. 2000
  • SDPSOL: a parser/solver for semidefinite programs with matrix structure Recent Advances in LMI Methods for Control Wu, S., P., Boyd, S. edited by El Ghaoui, L., Niculescu, S., I. 2000: 79–91
  • On achieving reduced error propagation sensitivity in DFE design via convex optimization 39th IEEE Conference on Decision and Control Kosut, R. L., Chung, W. Z., Johnson, C. R., Boyd, S. P. IEEE. 2000: 4320–4323

    View details for Web of Science ID 000172029000784

  • Simultaneous rate and power control in multirate multimedia CDMA systems IEEE 6th International Symposium on Spread Spectrum Techniques and Applications Kandukuri, S., Boyd, S. IEEE. 2000: 570–574

    View details for Web of Science ID 000165241800118

  • Low-authority controller design by means of convex optimization JOURNAL OF GUIDANCE CONTROL AND DYNAMICS Hassibi, A., How, J. P., Boyd, S. P. 1999; 22 (6): 862-872

    View details for Web of Science ID 000083658600015

  • Simple accurate expressions for planar spiral inductances IEEE JOURNAL OF SOLID-STATE CIRCUITS Mohan, S. S., Hershenson, M. D., Boyd, S. P., Lee, T. H. 1999; 34 (10): 1419-1424

    View details for Web of Science ID 000082884000013

  • Applications of semidefinite programming International Conference on High Performance Optimization Techniques (HPOPT 96) Vandenberghe, L., Boyd, S. ELSEVIER SCIENCE BV. 1999: 283–99

    View details for Web of Science ID 000078154800003

  • A path-following method for solving BMI problems in control Hassibi, A., How, J., Boyd, S. 1999
  • Policies for simultaneous estimation and optimization Lobo, M., Boyd, S. 1999
  • Design and optimization of LC oscillators Hershenson, M., Hajimiri, A., Mohan, S., Boyd, S., Lee, T. 1999
  • Optimization of inductor circuits via geometric programming Hershenson, M., Mohan, S., Boyd, S., Lee, T. 1999
  • Control of asynchronous dynamical systems with rate constraints on events Hassibi, A., Boyd, S., How, J. 1999
  • A class of Lyapunov functionals for analyzing hybrid dynamical systems Hassibi, A., Boyd, S., How, J. 1999
  • Crisis in scholarly publishing C-LIB subcommittee summary Report of subcommittee of the Stanford Academic Council Committee on Libraries (C-LIB), consisting of Stephen Boyd (chair), Doug Brutlag, Sam Chiu, Tim Lenoir, Assunta Pisani, and Andrew Herkovic. It was presented to C-LIB on 5/10/99, and to the Faculty Senate on 5/27/99. Boyd, S., Herkovic, A. 1999
  • Applications of second-order cone programming International-Linear-Algebra-Society Symposium on Linear Algebra in Control Theory, Signals and Image Processing Lobo, M. S., Vandenberghe, L., Boyd, S., Lebret, H. ELSEVIER SCIENCE INC. 1998: 193–228

    View details for Web of Science ID 000076918100012

  • Integer parameter estimation in linear models with applications to GPS IEEE TRANSACTIONS ON SIGNAL PROCESSING Hassibi, A., Boyd, S. 1998; 46 (11): 2938-2952

    View details for Web of Science ID 000076664100009

  • Control applications of nonlinear convex programming JOURNAL OF PROCESS CONTROL Boyd, S., Crusius, C., Hansson, A. 1998; 8 (5-6): 313-324

    View details for Web of Science ID 000076288700003

  • Determinant maximization with linear matrix inequality constraints SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Vandenberghe, L., Boyd, S., Wu, S. P. 1998; 19 (2): 499-533

    View details for Web of Science ID 000072539100014

  • Optimizing dominant time constant in RC circuits IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS Vandenberghe, L., Boyd, S., El Gamal, A. 1998; 17 (2): 110-125

    View details for Web of Science ID 000074258800004

  • Low-authority controller design via convex optimization 37th IEEE Conference on Decision and Control Hassibi, A., How, J., Boyd, S. IEEE. 1998: 140–145

    View details for Web of Science ID 000079708900025

  • FIR filter design via spectral factorization and convex optimization Applied and Computational Control, Signals and Circuits Wu, S., P., Boyd, S., Vandenberghe, L. 1998: 215–245
  • Control-relevant experiment design: a plant-friendly, LMI-based approach Cooley, B., Lee, J., Boyd, S. 1998
  • Connections between semi-infinite and semidefinite programming Vandenberghe, L., Boyd, S. 1998
  • An implementation of discrete multi-tone over slowly time-varying multiple-input/multiple-output channels IEEE Global Telecommunications Conference (GLOBECOM 98) Tehrani, A. M., Hassibi, A., Cioffi, J., Boyd, S. IEEE. 1998: 2806–2811

    View details for Web of Science ID 000081660200468

  • Optimal temperature profiles for post-exposure bake of photo-resist Conference on Metrology, Inspection, and Process Control for Microlithography XII Hansson, A., Boyd, S. SPIE - INT SOC OPTICAL ENGINEERING. 1998: 271–281

    View details for Web of Science ID 000075068300028

  • Quadratic stabilization and control of piecewise-linear systems American Control Conference Hassibi, A., Boyd, S. IEEE. 1998: 3659–3664

    View details for Web of Science ID 000075568200788

  • Robust solutions to l(1), l(2), and l(infinity) uncertain linear approximation problems using convex optimization American Control Conference Hindi, H. A., Boyd, S. P. IEEE. 1998: 3487–3491

    View details for Web of Science ID 000075568200749

  • Multiobjective H-2/H-infinity-optimal control via finite dimensional Q-parametrization and linear matrix inequalities American Control Conference Hindi, H. A., Hassibi, B., Boyd, S. P. IEEE. 1998: 3244–3249

    View details for Web of Science ID 000075568200698

  • GPCAD: A tool for CMOS op-amp synthesis IEEE/ACM International Conference on Computer-Aided Design Hershenson, M. D., Boyd, S. P., Lee, T. H. ASSOC COMPUTING MACHINERY. 1998: 296–303

    View details for Web of Science ID 000077729800045

  • Robust optimal control of linear discrete-time systems using primal-dual interior-point methods American Control Conference Hansson, A., Boyd, S. IEEE. 1998: 183–187

    View details for Web of Science ID 000075568200041

  • Synthesizing stability regions for systems with saturating actuators 37th IEEE Conference on Decision and Control Pare, T. E., Hindi, H., How, J. P., Boyd, S. P. IEEE. 1998: 1981–1982

    View details for Web of Science ID 000079708900392

  • Analysis of linear systems with saturation using convex optimization 37th IEEE Conference on Decision and Control Hindi, H., Boyd, S. IEEE. 1998: 903–908

    View details for Web of Science ID 000079708900177

  • Antenna array pattern synthesis via convex optimization IEEE TRANSACTIONS ON SIGNAL PROCESSING Lebret, H., Boyd, S. 1997; 45 (3): 526-532

    View details for Web of Science ID A1997WM48200002

  • Obstacle collision detection using best ellipsoid fit JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS Rimon, E., Boyd, S. P. 1997; 18 (2): 105-126

    View details for Web of Science ID A1997WN43800001

  • Optimal wire and transistor sizing for circuits with non-tree topology 1997 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 97) Vandenberghe, L., Boyd, S., Elgamal, A. I E E E, COMPUTER SOC PRESS. 1997: 252–259

    View details for Web of Science ID A1997BK01U00038

  • Efficient distance computation using best ellipsoid fit Journal of Intelligent and Robotic Systems, Kluwer Rimon, E., Boyd, S. 1997; 2 (18): 105-126
  • Semidefinite programming relaxations of non-convex problems in control and combinatorial optimization Communications, Computation, Control and Signal Processing Boyd, S., Vandenberghe, L. edited by Paulraj, A., Roychowdhuri, V., Schaper, C. A Tribute to Thomas Kailath. 1997: 279–288
  • A global BMI algorithm based on the generalized Benders decomposition Beran, E., Vandenberghe, L., Boyd, S. 1997
  • Semidefinite programming SIAM REVIEW Vandenberghe, L., Boyd, S. 1996; 38 (1): 49-95

    View details for Web of Science ID A1996UB18200003

  • Design and implementation of a parser/solver for SDPs with matrix structure 1996 IEEE International Symposium on Computer-Aided Control System Design Wu, S. P., Boyd, S. IEEE. 1996: 240–245

    View details for Web of Science ID A1996BG49L00042

  • Optimal excitation signal design for frequency domain system identification using semidefinite programming Javorzky, G., Kollar, I., Vandenberghe, L., Boyd, S., Wu, S., P. 1996
  • Control for advanced semiconductor device manufacturing: a case history The Control Handbook Kailath, T., Schaper, C., Cho, Y., Gyugyi, P., Norman, S., Park, P., Boyd, S. edited by Levine, W. CRC Press, Boca Raton, Fl.. 1996: 1243–1259
  • Integer parameter estimation in linear models with applications to GPS 35th IEEE Conference on Decision and Control Hassibi, A., Boyd, S. IEEE. 1996: 3245–3251

    View details for Web of Science ID A1996BH27F00701

  • FIR filter design via semidefinite programming and spectral factorization 35th IEEE Conference on Decision and Control Wu, S. P., Boyd, S., Vandenberghe, L. IEEE. 1996: 271–276

    View details for Web of Science ID A1996BH27F00064

  • A PRIMAL-DUAL POTENTIAL REDUCTION METHOD FOR PROBLEMS INVOLVING MATRIX INEQUALITIES MATHEMATICAL PROGRAMMING Vandenberghe, L., Boyd, S. 1995; 69 (1): 205-236

    View details for Web of Science ID A1995RU42800009

  • CRCD program: Convex optimization for engineering analysis and design 1995 American Control Conference Boyd, S., Vandenberghe, L. AMER AUTOMATIC CONTROL COUNCIL. 1995: 1069–1071

    View details for Web of Science ID A1995BD66H00226

  • EXISTENCE AND UNIQUENESS OF OPTIMAL MATRIX SCALINGS SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS Balakrishnan, V., Boyd, S. 1995; 16 (1): 29-39

    View details for Web of Science ID A1995QE10500003

  • GENERALIZED ACCESS-CONTROL STRATEGIES FOR INTEGRATED SERVICES TOKEN PASSING SYSTEMS IEEE TRANSACTIONS ON COMMUNICATIONS PANG, J. W., Tobagi, F. A., Boyd, S. 1994; 42 (8): 2561-2570

    View details for Web of Science ID A1994PB78800013

  • HISTORY OF LINEAR MATRIX INEQUALITIES IN CONTROL-THEORY 1994 American Control Conference Boyd, S., Feron, E., Balakrishnan, V., Elghaoui, L. I E E E. 1994: 31–34

    View details for Web of Science ID A1994BB17U00007

  • Tradeoffs in frequency-weighted H_infinity-control Balakrishnan, V., Boyd, S. 1994
  • Efficient convex optimization for engineering design Boyd, S., Vandenberghe, L., Grant, M. 1994
  • Existence and uniqueness of optimal matrix scalings Balakrishnan, V., Boyd, S. 1994
  • Linear Matrix Inequalities in System and Control Theory Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V. Society for Industrial and Applied Mathematics (SIAM). 1994
  • Linear Matrix Inequalities in Systems and Control Theory Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V. SIAM. 1994
  • IMPROVING STATIC PERFORMANCE ROBUSTNESS OF THERMAL PROCESSES 33rd IEEE Conference on Decision and Control Kabuli, M. G., Kosut, R. L., Boyd, S. IEEE. 1994: 62–66

    View details for Web of Science ID A1994BC17X00013

  • METHOD OF CENTERS FOR MINIMIZING GENERALIZED EIGENVALUES LINEAR ALGEBRA AND ITS APPLICATIONS Boyd, S., Elghaoui, L. 1993; 188: 63-111

    View details for Web of Science ID A1993LK50900004

  • CONTROL-SYSTEM ANALYSIS AND SYNTHESIS VIA LINEAR MATRIX INEQUALITIES 1993 AMERICAN CONTROL CONF Boyd, S., Balakrishnan, V., Feron, E., Elghaoui, L. I E E E. 1993: 2147–2154

    View details for Web of Science ID A1993BY87D00473

  • Linear matrix inequalities in system and control theory Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V. 1993
  • Control systems analysis and synthesis via linear matrix inequalities Boyd, S., Balakrishnan, V., Feron, E., El Ghaoui, L. 1993
  • Global optimization in control system analysis and design Control and Dynamic Systems: Advances in Theory and Aplications Balakrishnan, V., Boyd, S. edited by Leondes, C., T. Academic Press. 1993: 421–425
  • A polynomial-time algorithm for determining quadratic Lyapunov functions for nonlinear systems Vandenberghe, L., Boyd, S. 1993
  • Closed-loop convex formulation of classical and singular value loop shaping Appeared as a chapter in Control and Dynamical Systems: Digital and Numeric Techniques and Their Applications in Control Systems Barratt, C., Boyd, S. 1993: 1–24
  • SOLVING INTERPOLATION PROBLEMS VIA GENERALIZED EIGENVALUE MINIMIZATION 1993 AMERICAN CONTROL CONF Balakrishnan, V., Feron, E., Boyd, S., Elghaoui, L. I E E E. 1993: 2647–2648

    View details for Web of Science ID A1993BY87D00586

  • ON COMPUTING THE WORST-CASE PEAK GAIN OF LINEAR-SYSTEMS SYSTEMS & CONTROL LETTERS Balakrishnan, V., Boyd, S. 1992; 19 (4): 265-269

    View details for Web of Science ID A1992JU47200002

  • SET-MEMBERSHIP IDENTIFICATION OF SYSTEMS WITH PARAMETRIC AND NONPARAMETRIC UNCERTAINTY IEEE TRANSACTIONS ON AUTOMATIC CONTROL Kosut, R. L., Lau, M. K., Boyd, S. P. 1992; 37 (7): 929-941

    View details for Web of Science ID A1992JE07600005

  • EFFICIENT DISTANCE COMPUTATION USING BEST ELLIPSOID FIT 1992 IEEE INTERNATIONAL SYMP ON INTELLIGENT CONTROL Rimon, E., Boyd, S. P. I E E E. 1992: 360–365

    View details for Web of Science ID A1992BX94F00061

  • Dynamics and control of a rapid thermal multiprocessor Schaper, C., Cho, Y., Gyugyi, P., Hoffmann, G., Norman, S., Park, P., Boyd, S. 1992
  • On computing the worst-case peak gain of linear systems Balakrishnan, V., Boyd, S. 1992
  • Numerical methods for H_2 related problems Feron, E., Balakrishnan, V., Boyd, S., El Ghaoui, L. 1992
  • Multivariable feedback control of semiconductor wafer temperature Norman, S., Boyd, S. 1992
  • Computing bounds for the structured singular value via an interior point algorithm Balakrishnan, V., Feron, E., Boyd, S., El Ghaoui, L. 1992
  • Closed-loop convex analysis of performance limits for linear control systems Boyd, S., Barratt, C. 1992
  • Branch-and-bound algorithm for computing the minimum stability degree of parameter-dependent linear systems International Journal of Robust and Nonlinear Control Balakrishnan, V., Boyd, S., Balemi, S. 1992; 4 (1): 295-317
  • Interactive loop-shaping design of MIMO controllers Barratt, C., Boyd, S. 1992
  • MODELING AND CONTROL OF RAPID THERMAL-PROCESSING CONF ON RAPID THERMAL AND INTEGRATED PROCESSING Schaper, C., Cho, Y., Park, P., Norman, S., GYUGYI, P., HOFFMANN, G., BALEMI, S., Boyd, S., Franklin, G., KAILATH, T., Saraswat, K. SPIE - INT SOC OPTICAL ENGINEERING. 1992: 2–17

    View details for Web of Science ID A1992BV45H00001

  • EXISTENCE AND UNIQUENESS OF OPTIMAL MATRIX SCALINGS 31ST IEEE CONF ON DECISION AND CONTROL Balakrishnan, V., Boyd, S. I E E E. 1992: 2010–2011

    View details for Web of Science ID A1992BZ24X00458

  • DESIGN OF STABILIZING STATE-FEEDBACK FOR DELAY SYSTEMS VIA CONVEX-OPTIMIZATION 31ST IEEE CONF ON DECISION AND CONTROL Feron, E., Balakrishnan, V., Boyd, S. I E E E. 1992: 147–148

    View details for Web of Science ID A1992BZ24X00033

  • ON COMPUTING THE WORST-CASE PEAK GAIN OF LINEAR-SYSTEMS 31ST IEEE CONF ON DECISION AND CONTROL Balakrishnan, V., Boyd, S. I E E E. 1992: 2191–2192

    View details for Web of Science ID A1992BZ24X00497

  • ON OPTIMAL SIGNAL SETS FOR DIGITAL-COMMUNICATIONS WITH FINITE PRECISION AND AMPLITUDE CONSTRAINTS IEEE TRANSACTIONS ON COMMUNICATIONS Honig, M. L., Boyd, S. P., Gopinath, B., RANTAPAA, E. 1991; 39 (2): 249-255

    View details for Web of Science ID A1991FC43800016

  • ROBUST-CONTROL DESIGN FOR ELLIPSOIDAL PLANT SET 30TH IEEE CONF ON DECISION AND CONTROL / 1991 ANNUAL MEETING OF THE IEEE CONTROL SYSTEM SOC Lau, M. K., Boyd, S., Kosut, R. L., Franklin, G. F. I E E E. 1991: 291–296

    View details for Web of Science ID A1991BV05P00072

  • Linear Controller Design – Limits of Performance Boyd, S. Prentice-Hall. 1991
  • Robust control design for ellipsoidal plant set Lau, M., Boyd, S., Kosut, R., Franklin, G. 1991
  • Computation of the maximum H_infinity-norm of parameter-dependent linear systems by a branch and bound algorithm Balemi, S., Boyd, S., Balakrishnan, V. 1991
  • A robust control design for FIR plants with parameter set uncertainty Lau, M., Boyd, S., Kosut, R., Franklin, G. 1991
  • Linear Controller Design: Limits of Performance Boyd, S., Barratt, C. Prentice-Hall. 1991
  • COMPUTING THE MINIMUM STABILITY DEGREE OF PARAMETER-DEPENDENT LINEAR-SYSTEMS INTERNATIONAL WORKSHOP ON ROBUST CONTROL Balakrishnan, V., Boyd, S., BALEMI, S. CRC PRESS INC. 1991: 359–378

    View details for Web of Science ID A1991BX16Y00023

  • IMPROVEMENT OF TEMPERATURE UNIFORMITY IN RAPID THERMAL-PROCESSING SYSTEMS USING MULTIVARIABLE CONTROL SYMP ON RAPID THERMAL AND INTEGRATED PROCESSING Norman, S. A., Schaper, C. D., Boyd, S. P. MATERIALS RESEARCH SOC. 1991: 177–183

    View details for Web of Science ID A1991BV07P00024

  • COMPUTATION OF THE WORST-CASE COVARIANCE FOR LINEAR-SYSTEMS WITH UNCERTAIN PARAMETERS 30TH IEEE CONF ON DECISION AND CONTROL / 1991 ANNUAL MEETING OF THE IEEE CONTROL SYSTEM SOC Balakrishnan, V., Boyd, S. I E E E. 1991: 1941–1942

    View details for Web of Science ID A1991BV05P00447

  • A REGULARITY RESULT FOR THE SINGULAR-VALUES OF A TRANSFER-MATRIX AND A QUADRATICALLY CONVERGENT ALGORITHM FOR COMPUTING ITS L-INFINITY-NORM SYSTEMS & CONTROL LETTERS Boyd, S., Balakrishnan, V. 1990; 15 (1): 1-7

    View details for Web of Science ID A1990DT26800001

  • BOUNDS ON MAXIMUM THROUGHPUT FOR DIGITAL-COMMUNICATIONS WITH FINITE-PRECISION AND AMPLITUDE CONSTRAINTS IEEE TRANSACTIONS ON INFORMATION THEORY Honig, M. L., Steiglitz, K., Gopinath, B., Boyd, S. P. 1990; 36 (3): 472-484

    View details for Web of Science ID A1990DE94900002

  • LINEAR CONTROLLER-DESIGN - LIMITS OF PERFORMANCE VIA CONVEX-OPTIMIZATION PROCEEDINGS OF THE IEEE Boyd, S., Barratt, C., Norman, S. 1990; 78 (3): 529-574

    View details for Web of Science ID A1990DD20300004

  • PARAMETER SET ESTIMATION OF SYSTEMS WITH UNCERTAIN NONPARAMETRIC DYNAMICS AND DISTURBANCES 29th IEEE Conference on Decision and Control Lau, M. K., Kosut, R. L., Boyd, S. I E E E. 1990: 3162–3167

    View details for Web of Science ID A1990BA50L00684

  • Identification of systems with parametric and nonparametric uncertainty Kosut, R., Lau, M., Boyd, S. 1990
  • STABILITY ROBUSTNESS OF LINEAR-SYSTEMS TO REAL PARAMETRIC PERTURBATIONS 29th IEEE Conference on Decision and Control Elghaoui, L., Boyd, S. P. I E E E. 1990: 1247–1248

    View details for Web of Science ID A1990BA50L00273

  • A BRANCH-AND-BOUND METHODOLOGY FOR MATRIX POLYTOPE STABILITY PROBLEMS ARISING IN POWER-SYSTEMS 29th IEEE Conference on Decision and Control DeMarco, C. L., Balakrishnan, V., Boyd, S. I E E E. 1990: 3022–3027

    View details for Web of Science ID A1990BA50L00655

  • STRUCTURED AND SIMULTANEOUS LYAPUNOV FUNCTIONS FOR SYSTEM STABILITY PROBLEMS INTERNATIONAL JOURNAL OF CONTROL Boyd, S., Yang, Q. P. 1989; 49 (6): 2215-2240

    View details for Web of Science ID A1989AK07000025

  • STRUCTURED AND SIMULTANEOUS LYAPUNOV FUNCTIONS FOR SYSTEM STABILITY PROBLEMS INTERNATIONAL WORKSHOP ON ROBUSTNESS IN IDENTIFICATION AND CONTROL : UNKNOWN BUT BOUNDED Boyd, S., Yang, Q. P. PLENUM PRESS DIV PLENUM PUBLISHING CORP. 1989: 243–262

    View details for Web of Science ID A1989BP72H00016

  • Example of exact trade-offs in linear controller design Barratt, C., Boyd, S. 1989
  • A bisection method for computing the H_infinity-norm of a transfer matrix and related problems Mathematics of Control, Signals, and Systems Boyd, S., Balakrishnan, V., Kabamba, P. 1989; 3 (2): 207-219
  • NUMERICAL-SOLUTION OF A 2-DISK PROBLEM 8TH ANNUAL AMERICAN CONTROL CONF ON AUTOMATION AND CONTROL Norman, S. A., Boyd, S. P. AMER AUTOMATIC CONTROL COUNCIL. 1989: 1745–1747

    View details for Web of Science ID A1989BQ49K00315

  • A REGULARITY RESULT FOR THE SINGULAR-VALUES OF A TRANSFER-MATRIX AND A QUADRATICALLY CONVERGENT ALGORITHM FOR COMPUTING ITS L-INFINITY-NORM 28TH CONF AT THE 1989 ANNUAL MEETING OF THE IEEE : DECISION AND CONTROL Boyd, S., Balakrishnan, V. I E E E. 1989: 954–955

    View details for Web of Science ID A1989BP96Z00206

  • EXACT TRADEOFFS IN LTI CONTROLLER-DESIGN - AN EXAMPLE 8TH ANNUAL AMERICAN CONTROL CONF ON AUTOMATION AND CONTROL BARRATT, C. H., Boyd, S. P. AMER AUTOMATIC CONTROL COUNCIL. 1989: 1274–1279

    View details for Web of Science ID A1989BQ49K00227

  • A NEW CAD METHOD AND ASSOCIATED ARCHITECTURES FOR LINEAR CONTROLLERS IEEE TRANSACTIONS ON AUTOMATIC CONTROL Boyd, S. P., Balakrishnan, V., BARRATT, C. H., KHRAISHI, N. M., Li, X. M., Meyer, D. G., Norman, S. A. 1988; 33 (3): 268-283

    View details for Web of Science ID A1988M275000006

  • Perturbation bounds for structured robust stability Abed, E., Boyd, S. 1988
  • On computing the H_infinity-norm of a transfer matrix Boyd, S., Balakrishnan, V., Kabamba, P. 1988
  • On parametric H_infinity optimization Kabamba, P., Boyd, S. 1988
  • COMPARISON OF PEAK AND RMS GAINS FOR DISCRETE-TIME-SYSTEMS SYSTEMS & CONTROL LETTERS Boyd, S., Doyle, J. 1987; 9 (1): 1-6

    View details for Web of Science ID A1987J087800001

  • On the spectral density of some stochastic processes Open Problems in Communication and Computation Boyd, S., Hajela, D. edited by Cover, T., Gopinath, B. Springer Verlag. 1987: 191–198
  • Design of l1 optimal controllers Pearson, J., B., Boyd, S. 1987
  • NECESSARY AND SUFFICIENT CONDITIONS FOR PARAMETER CONVERGENCE IN ADAPTIVE-CONTROL AUTOMATICA Boyd, S., Sastry, S. S. 1986; 22 (6): 629-639

    View details for Web of Science ID A1986F957600002

  • A note on parametric and nonparametric uncertainties in control systems Boyd, S. 1986
  • A note on the order of l1-optimal compensators Meyer, D., Boyd, S. 1986
  • FADING MEMORY AND THE PROBLEM OF APPROXIMATING NONLINEAR OPERATORS WITH VOLTERRA SERIES IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS Boyd, S., Chua, L. O. 1985; 32 (11): 1150-1161

    View details for Web of Science ID A1985ATH9700007

  • Volterra series for nonlinear circuits Boyd, S., Chua, L., O. 1985
  • Low rate distributed quantization of noisy observations Gray, R., Boyd, S., Lookabaugh, T. 1985
  • UNIQUENESS OF CIRCUITS AND SYSTEMS CONTAINING ONE NONLINEARITY IEEE TRANSACTIONS ON AUTOMATIC CONTROL Boyd, S. P., Chua, L. O. 1985; 30 (7): 674-680

    View details for Web of Science ID A1985AJS1600008

  • Subharmonic Functions and Performance Bounds on Linear Time-Invariant Feedback Systems IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION Boyd, S., DESOER, C. A. 1985; 2 (2): 153-170

    View details for DOI 10.1093/imamci/2.2.153

    View details for Web of Science ID 000208453200006

  • Analytical Foundations of Volterra Series IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION Boyd, S., Chua, L. O., DESOER, C. A. 1984; 1 (3): 243-282

    View details for DOI 10.1093/imamci/1.3.243

    View details for Web of Science ID 000208452900003

  • Structures for nonlinear systems Boyd, S., Chua, L., O. 1984
  • ON PARAMETER CONVERGENCE IN ADAPTIVE-CONTROL SYSTEMS & CONTROL LETTERS Boyd, S., Sastry, S. 1983; 3 (6): 311-319

    View details for Web of Science ID A1983RY93800001

  • MEASURING VOLTERRA KERNELS IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS Boyd, S., Tang, Y. S., Chua, L. O. 1983; 30 (8): 571-577

    View details for Web of Science ID A1983RD51900007

  • Measuring Volterra kernels IEEE Transactions on Circuits and Systems Boyd, S., Tang, Y., S., Chua, L., O. 1983; 8 (30): 571-577
  • UNIQUENESS OF A BASIC NON-LINEAR STRUCTURE IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS Boyd, S., Chua, L. O. 1983; 30 (9): 648-651

    View details for Web of Science ID A1983RK49700006

  • ON THE PASSIVITY CRITERION FOR LTI N-PORTS INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS Boyd, S., Chua, L. O. 1982; 10 (4): 323-333

    View details for Web of Science ID A1982PM01100003

  • On optimal signal sets for digital communications with finite precision and amplitude constraints Honig, M., Boyd, S., Gopinath, B., Rantapaa, E. 1991, 1987
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