Yinyu Ye
Kwoh-Ting Li Professor in the School of Engineering, Emeritus
Management Science and Engineering
Web page: http://web.stanford.edu/people/yyye
Bio
Yinyu Ye is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering, Stanford University. He received the B.S. degree in System Engineering from the Huazhong University of Science and Technology, China, and the M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. Ye's research interests lie in the areas of optimization, complexity theory, algorithm design and analysis, and applications of mathematical programming, operations research and system engineering. He is also interested in developing optimization software for various real-world applications. Current research topics include Liner Programming Algorithms, Markov Decision Processes, Computational Game/Market Equilibrium, Metric Distance Geometry, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc. He is an INFORMS (The Institute for Operations Research and The Management Science) Fellow, and has received several research awards including the winner of the 2014 SIAG/Optimization Prize awarded every three years to the author(s) of the most outstanding paper, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2006 Farkas prize on Optimization, and the 2009 IBM Faculty Award. He has supervised numerous doctoral students at Stanford who received received the 2015 and 2013 Second Prize of INFORMS Nicholson Student Paper Competition, the 2013 INFORMS Computing Society Prize, the 2008 Nicholson Prize, and the 2006 and 2010 INFORMS Optimization Prizes for Young Researchers. Ye teaches courses on Optimization, Network and Integer Programming, Semidefinite Programming, etc. He has written extensively on Interior-Point Methods, Approximation Algorithms, Conic Optimization, and their applications; and served as a consultant or technical board member to a variety of industries, including MOSEK.
Honors & Awards
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SIAM Optimization Prize, SIAM (2015)
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Lectureship Prize (Inaugural Recipient), ISMP Tseng (2012)
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John von Neumann Theory Prize (Co-Recipient), INFORMS (2009)
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Faculty of the Year Award, Stanford Asian American Society (2007)
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Inaugural recipient of the Farkas Prize, INFORMS Optimization Society (2006)
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Fellow, INFORMS (November 6, 2006)
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Plenary speaker, International Symposium on Mathematical Programming, Berlin (2012)
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Plenary speaker, Workshop on Internet and Network Economics (2008)
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Semi-Plenary speaker, 17th International Symposium on Mathematical Programming, Atlanta (2000)
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Area Editor, Optimization & Engineering (2000)
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Associate Editor, Mathematics of Operations Research (1998-2001)
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Section Officer (Linear Programming), Institute for Operations Research and the Management Sciences (1997-2000)
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Co-organizer, DIMACS Princeton workshop on discrete optimizatio (1999)
Program Affiliations
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Center for East Asian Studies
Professional Education
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BS, Huazhong University of Science and Technology (HUST), China, Systems and Control (1982)
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MS, Stanford University, Engineering Economic Systems (1983)
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PhD, Stanford University, Engineering Economic Systems and Operations Research (1988)
Current Research and Scholarly Interests
My current research interests include Continuous and Discrete Optimization, Algorithm Development and Analyses, Algorithmic Game/Market Theory and Mechanism-Design, Markov Decision Process and Reinforcement Learning, Dynamic/Online Optimization and Resource Allocation, and Stochastic and Robust Decision Making. These areas have been the unique and core disciplines of MS&E, and extended to new application areas in AI, Machine Learning, Data Science, and Business Analytics.
2024-25 Courses
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Independent Studies (2)
- Curricular Practical Training
CME 390 (Aut, Win, Spr, Sum) - Ph.D. Research
CME 400 (Aut, Win, Spr, Sum)
- Curricular Practical Training
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Prior Year Courses
2023-24 Courses
- Introduction to Optimization
ENGR 62, MS&E 111, MS&E 211 (Aut) - Linear Programming
MS&E 310 (Aut) - Optimization in Data Science and Machine Learning
MS&E 314 (Win)
2021-22 Courses
- Introduction to Optimization (Accelerated)
ENGR 62X, MS&E 111X, MS&E 211X (Aut) - Linear Programming
MS&E 310 (Aut) - Optimization
CME 307, MS&E 311 (Win)
- Introduction to Optimization
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Sirui Lin, Saied Mahdian, Haoran Xu -
Doctoral Dissertation Advisor (AC)
Chunlin Sun -
Doctoral Dissertation Co-Advisor (AC)
Devansh Jalota -
Doctoral (Program)
Louis L.
All Publications
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Efficient Reinforcement Learning With Impaired Observability: Learning to Act With Delayed and Missing State Observations
IEEE TRANSACTIONS ON INFORMATION THEORY
2024; 70 (10): 7251-7272
View details for DOI 10.1109/TIT.2024.3416202
View details for Web of Science ID 001325287200014
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Data-driven aerodynamic shape design with distributionally robust optimization approaches
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
2024; 429
View details for DOI 10.1016/j.cma.2024.117131
View details for Web of Science ID 001257818700001
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An Enhanced Alternating Direction Method of Multipliers-Based Interior Point Method for Linear and Conic Optimization
INFORMS JOURNAL ON COMPUTING
2024
View details for DOI 10.1287/ijoc.2023.0017
View details for Web of Science ID 001236759800001
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Optimal Diagonal Preconditioning
OPERATIONS RESEARCH
2024
View details for DOI 10.1287/opre.2022.0592
View details for Web of Science ID 001180724300001
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A gradient descent akin method for constrained optimization: algorithms and applications
OPTIMIZATION METHODS & SOFTWARE
2024
View details for DOI 10.1080/10556788.2023.2285450
View details for Web of Science ID 001143083200001
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Sketched Newton Value Iteration for Large-Scale Markov Decision Processes
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2024: 13936-13944
View details for Web of Science ID 001241515300107
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Learning to Pivot as a Smart Expert
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2024: 8073-8081
View details for Web of Science ID 001239938200019
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Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2024: 16049-16057
View details for Web of Science ID 001239983500097
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A RIEMANNIAN DIMENSION-REDUCED SECOND-ORDER METHOD WITH APPLICATION IN SENSOR NETWORK LOCALIZATION
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2024; 46 (3): A2025-A2046
View details for DOI 10.1137/23M1567229
View details for Web of Science ID 001289519900009
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Worst-Case Iteration Bounds for Log Barrier Methods on Problems with Nonconvex Constraints
MATHEMATICS OF OPERATIONS RESEARCH
2023
View details for DOI 10.1287/moor.2020.0274
View details for Web of Science ID 001113185300001
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Optimization of Asset Allocation and Liquidation Time in Investment Decisions with VaR as a Risk Measure
COMPUTATIONAL ECONOMICS
2023
View details for DOI 10.1007/s10614-023-10451-x
View details for Web of Science ID 001049987800001
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Fisher markets with linear constraints: Equilibrium properties and efficient distributed algorithms
GAMES AND ECONOMIC BEHAVIOR
2023; 141: 223-260
View details for DOI 10.1016/j.geb.2023.06.007
View details for Web of Science ID 001039441900001
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Simple and fast algorithm for binary integer and online linear programming
MATHEMATICAL PROGRAMMING
2022
View details for DOI 10.1007/s10107-022-01880-x
View details for Web of Science ID 000847620700001
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An Improved Analysis of LP-Based Control for Revenue Management
OPERATIONS RESEARCH
2022
View details for DOI 10.1287/opre.2022.2358
View details for Web of Science ID 000841481500001
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Optimization and Operations Research in Mitigation of a Pandemic
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF CHINA
2022; 10 (2): 289-304
View details for DOI 10.1007/s40305-022-00391-y
View details for Web of Science ID 000793649600001
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High-Dimensional Learning Under Approximate Sparsity with Applications to Nonsmooth Estimation and Regularized Neural Networks
OPERATIONS RESEARCH
2022
View details for DOI 10.1287/opre.2021.2217
View details for Web of Science ID 000803709700001
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Distributed Stochastic Optimization with Large Delays
MATHEMATICS OF OPERATIONS RESEARCH
2021
View details for DOI 10.1287/moor.2021.1200
View details for Web of Science ID 000731960500001
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Online Linear Programming: Dual Convergence, New Algorithms, and Regret Bounds
OPERATIONS RESEARCH
2021
View details for DOI 10.1287/opre.2021.2164
View details for Web of Science ID 000731969400001
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Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs (vol 181, pg 1, 2020)
MATHEMATICAL PROGRAMMING
2021
View details for DOI 10.1007/s10107-021-01684-5
View details for Web of Science ID 000670874000001
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Variance reduced value iteration and faster algorithms for solving Markov decision processes
NAVAL RESEARCH LOGISTICS
2021
View details for DOI 10.1002/nav.21992
View details for Web of Science ID 000642314100001
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The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2021
View details for Web of Science ID 000683104606047
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A Mathematical Programming Formulation for Optimal Load Shifting of Electricity Demand for the Smart Grid
IEEE TRANSACTIONS ON BIG DATA
2020; 6 (4): 638–51
View details for DOI 10.1109/TBDATA.2016.2639528
View details for Web of Science ID 000591809700003
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An ADMM-based interior-point method for large-scale linear programming
OPTIMIZATION METHODS & SOFTWARE
2020
View details for DOI 10.1080/10556788.2020.1821200
View details for Web of Science ID 000572518800001
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Managing randomization in the multi-block alternating direction method of multipliers for quadratic optimization
MATHEMATICAL PROGRAMMING COMPUTATION
2020
View details for DOI 10.1007/s12532-020-00192-5
View details for Web of Science ID 000572298400001
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On the complexity of an expanded Tarski's fixed point problem under the componentwise ordering (vol 732, pg 26, 2018)
THEORETICAL COMPUTER SCIENCE
2020; 817: 80
View details for DOI 10.1016/j.tcs.2019.03.014
View details for Web of Science ID 000524287900009
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Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs
MATHEMATICAL PROGRAMMING
2020; 181 (1): 1–17
View details for DOI 10.1007/s10107-019-01367-2
View details for Web of Science ID 000531046500001
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On the Efficiency of Random Permutation for ADMM and Coordinate Descent
MATHEMATICS OF OPERATIONS RESEARCH
2020; 45 (1): 233–71
View details for DOI 10.1287/moor.2019.0990
View details for Web of Science ID 000512979600011
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MULTILEVEL MONTE CARLO SAMPLING ON HETEROGENEOUS COMPUTER ARCHITECTURES
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
2020; 10 (6): 575–94
View details for DOI 10.1615/Int.J.UncertaintyQuantification.2020033179
View details for Web of Science ID 000599583800005
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Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity
ADDISON-WESLEY PUBL CO. 2020
View details for Web of Science ID 000559931303021
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On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods
MATHEMATICAL PROGRAMMING
2019
View details for DOI 10.1007/s10107-019-01454-4
View details for Web of Science ID 000574702400001
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Towards solving 2-TBSG efficiently
OPTIMIZATION METHODS & SOFTWARE
2019
View details for DOI 10.1080/10556788.2019.1695131
View details for Web of Science ID 000501692900001
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Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary
MATHEMATICAL PROGRAMMING
2019; 178 (1-2): 263–99
View details for DOI 10.1007/s10107-018-1290-4
View details for Web of Science ID 000495020200007
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Sample Average Approximation with Sparsity-Inducing Penalty for High-Dimensional Stochastic Programming.
Mathematical programming
2019; 78 (1-2): 69–108
Abstract
The theory on the traditional sample average approximation (SAA) scheme for stochastic programming (SP) dictates that the number of samples should be polynomial in the number of problem dimensions in order to ensure proper optimization accuracy. In this paper, we study a modification to the SAA in the scenario where the global minimizer is either sparse or can be approximated by a sparse solution. By making use of a regularization penalty referred to as the folded concave penalty (FCP), we show that, if an FCP-regularized SAA formulation is solved locally, then the required number of samples can be significantly reduced in approximating the global solution of a convex SP: the sample size is only required to be poly-logarithmic in the number of dimensions. The efficacy of the FCP regularizer for nonconvex SPs is also discussed. As an immediate implication of our result, a flexible class of folded concave penalized sparse M-estimators in high-dimensional statistical learning may yield a sound performance even when the problem dimension cannot be upper-bounded by any polynomial function of the sample size.
View details for DOI 10.1007/s10107-018-1278-0
View details for PubMedID 31680704
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Worst-case complexity of cyclic coordinate descent: O(n(2)) gap with randomized version
MATHEMATICAL PROGRAMMING
2019
View details for DOI 10.1007/s10107-019-01437-5
View details for Web of Science ID 000492250700001
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Approximation Hardness for A Class of Sparse Optimization Problems
JOURNAL OF MACHINE LEARNING RESEARCH
2019; 20
View details for Web of Science ID 000464271900001
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Interior-point Methods Strike Back: Solving the Wasserstein Barycenter Problem
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019
View details for Web of Science ID 000534424306085
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Extended ADMM and BCD for nonseparable convex minimization models with quadratic coupling terms: convergence analysis and insights
MATHEMATICAL PROGRAMMING
2019; 173 (1-2): 37–77
View details for DOI 10.1007/s10107-017-1205-9
View details for Web of Science ID 000456970900002
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On the complexity of an expanded Tarski's fixed point problem under the componentwise ordering
THEORETICAL COMPUTER SCIENCE
2018; 732: 26–45
View details for DOI 10.1016/jscs.2018.04.021
View details for Web of Science ID 000433999200003
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A computation study on an integrated alternating direction method of multipliers for large scale optimization
OPTIMIZATION LETTERS
2018; 12 (1): 3–15
View details for DOI 10.1007/s11590-017-1116-y
View details for Web of Science ID 000419552800002
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Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes
ASSOC COMPUTING MACHINERY. 2018: 770–87
View details for Web of Science ID 000483921200051
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Learning in Games with Lossy Feedback
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018
View details for Web of Science ID 000461823305017
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Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018
View details for Web of Science ID 000461823305022
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ON DOUBLY POSITIVE SEMIDEFINITE PROGRAMMING RELAXATIONS
GLOBAL SCIENCE PRESS. 2018: 391–403
View details for DOI 10.4208/jcm.1708-m2017-0130
View details for Web of Science ID 000455995700005
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Special issue on "Modern Optimization and Applications" Preface
JOURNAL OF COMPUTATIONAL MATHEMATICS
2018; 36 (3): I-II
View details for Web of Science ID 000455995700001
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Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.
Mathematical programming
2017; 166 (1-2): 207-240
Abstract
This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S3ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S3ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S3ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee the S3ONC admits FPTAS.
View details for DOI 10.1007/s10107-017-1114-y
View details for PubMedID 29225375
View details for PubMedCentralID PMC5720392
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On a New SDP-SOCP Method for Acoustic Source Localization Problem
ACM TRANSACTIONS ON SENSOR NETWORKS
2016; 12 (4)
View details for DOI 10.1145/2968449
View details for Web of Science ID 000388853800011
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Hidden-City Ticketing: The Cause and Impact
TRANSPORTATION SCIENCE
2016; 50 (1): 288-305
View details for DOI 10.1287/trsc.2015.0587
View details for Web of Science ID 000375655400019
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The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
MATHEMATICAL PROGRAMMING
2016; 155 (1-2): 57-79
View details for DOI 10.1007/s10107-014-0826-5
View details for Web of Science ID 000367695200002
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The Simplex Method is Strongly Polynomial for Deterministic Markov Decision Processes
MATHEMATICS OF OPERATIONS RESEARCH
2015; 40 (4): 859-868
View details for DOI 10.1287/moor.2014.0699
View details for Web of Science ID 000367895700004
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A fixed point iterative approach to integer programming and its distributed computation
FIXED POINT THEORY AND APPLICATIONS
2015
View details for DOI 10.1186/s13663-015-0429-8
View details for Web of Science ID 000366020200004
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A homogeneous interior-point algorithm for nonsymmetric convex conic optimization
MATHEMATICAL PROGRAMMING
2015; 150 (2): 391-422
View details for DOI 10.1007/s10107-014-0773-1
View details for Web of Science ID 000351522700007
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Simultaneous beam sampling and aperture shape optimization for SPORT.
Medical physics
2015; 42 (2): 1012-?
Abstract
Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes.The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution.A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%.The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.
View details for DOI 10.1118/1.4906253
View details for PubMedID 25652514
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Complexity analysis of interior point algorithms for non-Lipschitz and nonconvex minimization
MATHEMATICAL PROGRAMMING
2015; 149 (1-2): 301-327
View details for DOI 10.1007/s10107-014-0753-5
View details for Web of Science ID 000347830300011
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The Value of Stochastic Modeling in Two-Stage Stochastic Programs with Cost Uncertainty
OPERATIONS RESEARCH
2014; 62 (6): 1377-1393
View details for DOI 10.1287/opre.2014.1318
View details for Web of Science ID 000346153600012
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Space tensor conic programming
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
2014; 59 (1-2): 307-319
View details for DOI 10.1007/s10589-013-9577-0
View details for Web of Science ID 000341495800016
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A Levenberg-Marquardt method with approximate projections
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
2014; 59 (1-2): 5-26
View details for DOI 10.1007/s10589-013-9573-4
View details for Web of Science ID 000341495800002
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Waterflood management using two-stage optimization with streamline simulation
COMPUTATIONAL GEOSCIENCES
2014; 18 (3-4): 483-504
View details for DOI 10.1007/s10596-014-9404-4
View details for Web of Science ID 000341492200015
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A Dynamic Near-Optimal Algorithm for Online Linear Programming
OPERATIONS RESEARCH
2014; 62 (4): 876-890
View details for DOI 10.1287/opre.2014.1289
View details for Web of Science ID 000343248400011
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Close the Gaps: A Learning-While-Doing Algorithm for Single-Product Revenue Management Problems
OPERATIONS RESEARCH
2014; 62 (2): 318-331
View details for DOI 10.1287/opre.2013.1245
View details for Web of Science ID 000335394200007
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Complexity of unconstrained minimization
MATHEMATICAL PROGRAMMING
2014; 143 (1-2): 371-383
View details for DOI 10.1007/s10107-012-0613-0
View details for Web of Science ID 000330038300014
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Analytical Results and Efficient Algorithm for Optimal Portfolio Deleveraging with Market Impact
OPERATIONS RESEARCH
2014; 62 (1): 195-206
View details for DOI 10.1287/opre.2013.1222
View details for Web of Science ID 000332013300013
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A Dynamic Algorithm for Facilitated Charging of Plug-In Electric Vehicles
IEEE TRANSACTIONS ON SMART GRID
2013; 4 (4): 1772-1779
View details for DOI 10.1109/TSG.2012.2233768
View details for Web of Science ID 000328064100004
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Newsvendor optimization with limited distribution information
OPTIMIZATION METHODS & SOFTWARE
2013; 28 (3): 640-667
View details for DOI 10.1080/10556788.2013.768994
View details for Web of Science ID 000320093700016
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On stress matrices of (d+1)-lateration frameworks in general position
MATHEMATICAL PROGRAMMING
2013; 137 (1-2): 1-17
View details for DOI 10.1007/s10107-011-0480-0
View details for Web of Science ID 000313797100001
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On affine motions and bar frameworks in general position
LINEAR ALGEBRA AND ITS APPLICATIONS
2013; 438 (1): 31-36
View details for DOI 10.1016/j.laa.2012.08.031
View details for Web of Science ID 000312682900004
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Beyond Convex Relaxation: A Polynomial-Time Non-Convex Optimization Approach to Network Localization
32nd IEEE INFOCOM Conference
IEEE. 2013: 2499–2507
View details for Web of Science ID 000326335202070
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THE CUBIC SPHERICAL OPTIMIZATION PROBLEMS
MATHEMATICS OF COMPUTATION
2012; 81 (279): 1513-1525
View details for Web of Science ID 000305099000011
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A FPTAS for computing a symmetric Leontief competitive economy equilibrium
MATHEMATICAL PROGRAMMING
2012; 131 (1-2): 113-129
View details for DOI 10.1007/s10107-010-0348-8
View details for Web of Science ID 000299180900006
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A variational principle for computing nonequilibrium fluxes and potentials in genome-scale biochemical networks
JOURNAL OF THEORETICAL BIOLOGY
2012; 292: 71-77
Abstract
We derive a convex optimization problem on a steady-state nonequilibrium network of biochemical reactions, with the property that energy conservation and the second law of thermodynamics both hold at the problem solution. This suggests a new variational principle for biochemical networks that can be implemented in a computationally tractable manner. We derive the Lagrange dual of the optimization problem and use strong duality to demonstrate that a biochemical analogue of Tellegen's theorem holds at optimality. Each optimal flux is dependent on a free parameter that we relate to an elementary kinetic parameter when mass action kinetics is assumed.
View details for DOI 10.1016/j.jtbi.2011.09.029
View details for Web of Science ID 000297450100008
View details for PubMedID 21983269
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Price of Correlations in Stochastic Optimization
OPERATIONS RESEARCH
2012; 60 (1): 150-162
View details for DOI 10.1287/opre.1110.1011
View details for Web of Science ID 000302113900013
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Geometric rounding: a dependent randomized rounding scheme
JOURNAL OF COMBINATORIAL OPTIMIZATION
2011; 22 (4): 699-725
View details for DOI 10.1007/s10878-010-9320-z
View details for Web of Science ID 000296520200017
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The Simplex and Policy-Iteration Methods Are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate
MATHEMATICS OF OPERATIONS RESEARCH
2011; 36 (4): 593-603
View details for DOI 10.1287/moor.1110.0516
View details for Web of Science ID 000296977700001
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An interior-point path-following algorithm for computing a Leontief economy equilibrium
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
2011; 50 (2): 223-236
View details for DOI 10.1007/s10589-010-9332-8
View details for Web of Science ID 000295574600003
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A note on the complexity of L-p minimization
MATHEMATICAL PROGRAMMING
2011; 129 (2): 285-299
View details for DOI 10.1007/s10107-011-0470-2
View details for Web of Science ID 000295785000006
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An Optimization Approach to Improving Collections of Shape Maps
COMPUTER GRAPHICS FORUM
2011; 30 (5): 1481-1491
View details for DOI 10.1111/j.1467-8659.2011.02022.x
View details for Web of Science ID 000293524100012
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A Unified Framework for Dynamic Prediction Market Design
OPERATIONS RESEARCH
2011; 59 (3): 550-568
View details for DOI 10.1287/opre.1110.0922
View details for Web of Science ID 000292639000003
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Statistical ranking and combinatorial Hodge theory
MATHEMATICAL PROGRAMMING
2011; 127 (1): 203-244
View details for DOI 10.1007/s10107-010-0419-x
View details for Web of Science ID 000288371400009
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Computing an Integer Point in a Class of Polytopes
10th International Symposium on Operations Research and Its Applications in Engineering, Technology and Management (ISO-RA)
WORLD PUBLISHING CORPORATION. 2011: 258–263
View details for Web of Science ID 000306631500031
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ON EQUILIBRIUM PRICING AS CONVEX OPTIMIZATION
JOURNAL OF COMPUTATIONAL MATHEMATICS
2010; 28 (5): 569-578
View details for DOI 10.4208/jcm.1003-m0001
View details for Web of Science ID 000281879100001
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Semidefinite Relaxation of Quadratic Optimization Problems
IEEE SIGNAL PROCESSING MAGAZINE
2010; 27 (3): 20-34
View details for DOI 10.1109/MSP.2010.936019
View details for Web of Science ID 000276819100006
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Special Issue in Memory of Alexander Rubinov
PACIFIC JOURNAL OF OPTIMIZATION
2010; 6 (2)
View details for Web of Science ID 000278611300001
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Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
OPERATIONS RESEARCH
2010; 58 (3): 595-612
View details for DOI 10.1287/opre.1090.0741
View details for Web of Science ID 000278912100006
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Dynamic Spectrum Management With the Competitive Market Model
IEEE TRANSACTIONS ON SIGNAL PROCESSING
2010; 58 (4): 2442-2446
View details for DOI 10.1109/TSP.2009.2039820
View details for Web of Science ID 000275370800048
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A novel fluence map optimization model incorporating leaf sequencing constraints
PHYSICS IN MEDICINE AND BIOLOGY
2010; 55 (4): 1243-1264
Abstract
A novel fluence map optimization model incorporating leaf sequencing constraints is proposed to overcome the drawbacks of the current objective inside smoothing models. Instead of adding a smoothing item to the objective function, we add the total number of monitor unit (TNMU) requirement directly to the constraints which serves as an important factor to balance the fluence map optimization and leaf sequencing optimization process at the same time. Consequently, we formulate the fluence map optimization models for the trailing (left) leaf synchronized, leading (right) leaf synchronized and the interleaf motion constrained non-synchronized leaf sweeping schemes, respectively. In those schemes, the leaves are all swept unidirectionally from left to right. Each of those models is turned into a linear constrained quadratic programming model which can be solved effectively by the interior point method. Those new models are evaluated with two publicly available clinical treatment datasets including a head-neck case and a prostate case. As shown by the empirical results, our models perform much better in comparison with two recently emerged smoothing models (the total variance smoothing model and the quadratic smoothing model). For all three leaf sweeping schemes, our objective dose deviation functions increase much slower than those in the above two smoothing models with respect to the decreasing of the TNMU. While keeping plans in the similar conformity level, our new models gain much better performance on reducing TNMU.
View details for DOI 10.1088/0031-9155/55/4/023
View details for Web of Science ID 000274206800023
View details for PubMedID 20124655
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UNIVERSAL RIGIDITY AND EDGE SPARSIFICATION FOR SENSOR NETWORK LOCALIZATION
SIAM JOURNAL ON OPTIMIZATION
2010; 20 (6): 3059-3081
View details for DOI 10.1137/090772009
View details for Web of Science ID 000285547100015
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LOWER BOUND THEORY OF NONZERO ENTRIES IN SOLUTIONS OF l(2)-l(p) MINIMIZATION
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2010; 32 (5): 2832-2852
View details for DOI 10.1137/090761471
View details for Web of Science ID 000283293500030
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The Complexity of Determining the Uniqueness of Tarski's Fixed Point under the Lexicographic Ordering
6th International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2010: 455–461
View details for Web of Science ID 000290644400038
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Universal Rigidity: Towards Accurate and Efficient Localization of Wireless Networks
Conference on IEEE INFOCOM
IEEE. 2010
View details for Web of Science ID 000287416300158
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Correlation Robust Stochastic Optimization
21st Annual ACM/SIAM Symposium on Discrete Algorithms
SIAM. 2010: 1087–1096
View details for Web of Science ID 000280699900088
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Finding Equitable Convex Partitions of Points in a Polygon Efficiently
ACM TRANSACTIONS ON ALGORITHMS
2010; 6 (4)
View details for DOI 10.1145/1824777.1824792
View details for Web of Science ID 000284382400016
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Stochastic Combinatorial Optimization with Controllable Risk Aversion Level
MATHEMATICS OF OPERATIONS RESEARCH
2009; 34 (3): 522-537
View details for DOI 10.1287/moor.1090.0390
View details for Web of Science ID 000269484000002
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Conceptual formulation on four-dimensional inverse planning for intensity modulated radiation therapy
PHYSICS IN MEDICINE AND BIOLOGY
2009; 54 (13): N255-N266
Abstract
Four-dimensional computed tomography (4DCT) offers an extra dimension of 'time' on the three-dimensional patient model with which we can incorporate target motion in radiation treatment (RT) planning and delivery in various ways such as in the concept of internal target volume, in gated treatment or in target tracking. However, for all these methodologies, different phases are essentially considered as non-interconnected independent phases for the purpose of optimization, in other words, the 'time' dimension has yet to be incorporated explicitly in the optimization algorithm and fully exploited. In this note, we have formulated a new 4D inverse planning technique that treats all the phases in the 4DCT as one single entity in the optimization. The optimization is formulated as a quadratic problem for disciplined convex programming that enables the problem to be analyzed and solved efficiently. In the proof-of-principle examples illustrated, we show that the temporal information of the spatial relation of the target and organs at risk could be 'exchanged' amongst different phases so that an appropriate weighting of dose deposition could be allocated to each phase, thus enabling a treatment with a tight target margin and a full duty cycle otherwise not achievable by either of the aforementioned methodologies. Yet there are practical issues to be solved in the 4D RT planning and delivery. The 4D concept in the optimization we have formulated here does provide insight on how the 'time' dimension can be exploited in the 4D optimization process.
View details for DOI 10.1088/0031-9155/54/13/N01
View details for Web of Science ID 000267137200025
View details for PubMedID 19521008
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An edge-reduction algorithm for the vertex cover problem
OPERATIONS RESEARCH LETTERS
2009; 37 (3): 181-186
View details for DOI 10.1016/j.orl.2009.01.010
View details for Web of Science ID 000266360900009
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Solving Min-Max Multi-Depot Vehicle Routing Problem
Workshop on Global Optimization - Methods and Applications
AMER MATHEMATICAL SOC. 2009: 31–46
View details for Web of Science ID 000270995500003
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A Unified Framework for Dynamic Pari-Mutuel Information Market Design
10th ACM Conference on Electronic Commerce (EC-2009)
ASSOC COMPUTING MACHINERY. 2009: 255–264
View details for Web of Science ID 000294744400030
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BIQUADRATIC OPTIMIZATION OVER UNIT SPHERES AND SEMIDEFINITE PROGRAMMING RELAXATIONS
SIAM JOURNAL ON OPTIMIZATION
2009; 20 (3): 1286-1310
View details for DOI 10.1137/080729104
View details for Web of Science ID 000277836500009
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Budget Allocation in a Competitive Communication Spectrum Economy
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
2009
View details for DOI 10.1155/2009/963717
View details for Web of Science ID 000266315900001
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Using total-variation regularization for intensity modulated radiation therapy inverse planning with field-specific numbers of segments
PHYSICS IN MEDICINE AND BIOLOGY
2008; 53 (23): 6653-6672
Abstract
Currently, there are two types of treatment planning algorithms for intensity modulated radiation therapy (IMRT). The beamlet-based algorithm generates beamlet intensity maps with high complexity, resulting in large numbers of segments in the delivery after a leaf-sequencing algorithm is applied. The segment-based direct aperture optimization (DAO) algorithm includes the physical constraints of the deliverable apertures in the calculation, and achieves a conformal dose distribution using a small number of segments. However, the number of segments is pre-fixed in most of the DAO approaches, and the typical random search scheme in the optimization is computationally intensive. A regularization-based algorithm is proposed to overcome the drawbacks of the DAO method. Instead of smoothing the beamlet intensity maps as in many existing methods, we include a total-variation term in the optimization objective function to reduce the number of signal levels of the beam intensity maps. An aperture rectification algorithm is then applied to generate a significantly reduced number of deliverable apertures. As compared to the DAO algorithm, our method has an efficient form of quadratic optimization, with an additional advantage of optimizing field-specific numbers of segments based on the modulation complexity. The proposed approach is evaluated using two clinical cases. Under the condition that the clinical acceptance criteria of the treatment plan are satisfied, for the prostate patient, the total number of segments for five fields is reduced from 61 using the Eclipse planning system to 35 using the proposed algorithm; for the head and neck patient, the total number of segments for seven fields is reduced from 107 to 28. The head and neck result is also compared to that using an equal number of four segments for each field. The comparison shows that using field-specific numbers of segments achieves a much improved dose distribution.
View details for DOI 10.1088/0031-9155/53/23/002
View details for Web of Science ID 000260859000002
View details for PubMedID 18997262
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The complexity of equilibria: Hardness results for economies via a correspondence with games
Workshop on Excursions in Algoritmics
ELSEVIER SCIENCE BV. 2008: 188–98
View details for DOI 10.1016/j.tcs.2008.08.007
View details for Web of Science ID 000261416700010
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A Unified Theorem on SDP Rank Reduction
MATHEMATICS OF OPERATIONS RESEARCH
2008; 33 (4): 910-920
View details for DOI 10.1287/moor.1080.0326
View details for Web of Science ID 000261150000009
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Preface
ALGORITHMICA
2008; 52 (1): 1-2
View details for DOI 10.1007/s00453-007-9001-1
View details for Web of Science ID 000258107400001
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FURTHER RELAXATIONS OF THE SEMIDEFINITE PROGRAMMING APPROACH TO SENSOR NETWORK LOCALIZATION
SIAM JOURNAL ON OPTIMIZATION
2008; 19 (2): 655-673
View details for DOI 10.1137/060669395
View details for Web of Science ID 000260849600008
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A FPTAS for Computing a Symmetric Leontief Competitive Economy Equilibrium
4th International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2008: 31–40
View details for Web of Science ID 000262046200003
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Parimutuel Betting on Permutations
4th International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2008: 126–137
View details for Web of Science ID 000262046200012
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A distributed SDP approach for large-scale noisy anchor-free graph realization with applications to molecular conformation
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2008; 30 (3): 1251-1277
View details for DOI 10.1137/05062754X
View details for Web of Science ID 000255500500007
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Algorithm 875: DSDP5 - Software for semidefinite programming
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
2008; 34 (3)
View details for DOI 10.1145/1356052.1356057
View details for Web of Science ID 000256338400005
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Fast aperture-based inverse treatment planning using mixed integer and quadratic optimization
50th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO)
ELSEVIER SCIENCE INC. 2008: S675–S675
View details for Web of Science ID 000258805302411
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A path to the Arrow-Debreu competitive market equilibrium
5th Brazilian Workshop on Continuous Optimization
SPRINGER. 2008: 315–48
View details for DOI 10.1007/s10107-006-0065-5
View details for Web of Science ID 000247429500014
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Exchange market equilibria with Leontief's utility: Freedom of pricing leads to rationality
1st International Workshop on Internet and Network Economics
ELSEVIER SCIENCE BV. 2007: 134–42
View details for DOI 10.1016/j.tcs.2007.02.016
View details for Web of Science ID 000247663400002
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On approximating complex quadratic optimization problems via semidefinite programming relaxations
11th IPCO Conference
SPRINGER. 2007: 93–110
View details for DOI 10.1007/s10107-006-0064-6
View details for Web of Science ID 000244889700006
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A ubiquitin ligase transfers preformed polyubiquitin chains from a conjugating enzyme to a substrate
NATURE
2007; 446 (7133): 333-337
Abstract
In eukaryotic cells, many short-lived proteins are conjugated with Lys 48-linked ubiquitin chains and degraded by the proteasome. Ubiquitination requires an activating enzyme (E1), a conjugating enzyme (E2) and a ligase (E3). Most ubiquitin ligases use either a HECT (homologous to E6-associated protein C terminus) or a RING (really interesting new gene) domain to catalyse polyubiquitination, but the mechanism of E3 catalysis is poorly defined. Here we dissect this process using mouse Ube2g2 (E2; identical at the amino acid level to human Ube2g2) and human gp78 (E3), an endoplasmic reticulum (ER)-associated conjugating system essential for the degradation of misfolded ER proteins. We demonstrate by expressing recombinant proteins in Escherichia coli that Ube2g2/gp78-mediated polyubiquitination involves preassembly of Lys 48-linked ubiquitin chains at the catalytic cysteine of Ube2g2. The growth of Ube2g2-anchored ubiquitin chains seems to be mediated by an aminolysis-based transfer reaction between two Ube2g2 molecules that each carries a ubiquitin moiety in its active site. Intriguingly, polyubiquitination of a substrate can be achieved by transferring preassembled ubiquitin chains from Ube2g2 to a lysine residue in a substrate.
View details for DOI 10.1038/nature05542
View details for Web of Science ID 000244892900049
View details for PubMedID 17310145
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Theory of semidefinite programming for sensor network localization
16th Annual ACM-SIAM Symposium on Discrete Algorithms
SPRINGER. 2007: 367–84
View details for DOI 10.1007/s10107-006-0040-1
View details for Web of Science ID 000243908500008
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Pari-mutuel markets: Mechanisms and performance
3rd International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2007: 82–95
View details for Web of Science ID 000252182500011
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Approximating the radii of point sets
SIAM JOURNAL ON COMPUTING
2007; 36 (6): 1764-1776
View details for DOI 10.1137/050627472
View details for Web of Science ID 000246299400012
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Semidefinite programming approaches for sensor network localization with noisy distance measurements
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
2006; 3 (4): 360-371
View details for DOI 10.1109/TASE.2006.877401
View details for Web of Science ID 000241124200003
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Improved complexity results on solving real-number linear feasibility problems
MATHEMATICAL PROGRAMMING
2006; 106 (2): 339-363
View details for DOI 10.1007/s10107-005-0610-7
View details for Web of Science ID 000235062200007
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Lot-sizing scheduling with batch setup times
JOURNAL OF SCHEDULING
2006; 9 (3): 299-310
View details for DOI 10.1007/s10951-006-8265-7
View details for Web of Science ID 000237397600006
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Semidefinite Programming Based Algorithms for Sensor Network Localization
ACM TRANSACTIONS ON SENSOR NETWORKS
2006; 2 (2)
View details for Web of Science ID 000205012900003
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Stochastic combinatorial optimization with controllable risk aversion level - (Extended abstract)
9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems/10th International Workshop on Randomization and Computation
SPRINGER-VERLAG BERLIN. 2006: 224–235
View details for Web of Science ID 000240348600020
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A Semidefinite Programming Approach to Tensegrity Theory and Realizability of Graphs
17th ACM-SIAM Symposium on Discrete Algorithms
SIAM. 2006: 766–775
View details for Web of Science ID 000281596300084
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Distributed method for solving semidefinite programs arising from ad hoc wireless sensor network localization
Conference on Multiscale Optimization Methods and Applications
SPRINGER. 2006: 69–84
View details for Web of Science ID 000234830500002
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Area Editors' Statements
OPERATIONS RESEARCH
2006; 54 (1): 5-10
View details for DOI 10.1287/opre.1050.0269
View details for Web of Science ID 000235596200002
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SpaseLoc: An adaptive subproblem algorithm for scalable wireless sensor network localization
SIAM JOURNAL ON OPTIMIZATION
2006; 17 (4): 1102-1128
View details for DOI 10.1137/040621600
View details for Web of Science ID 000244631800007
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Approximation algorithms for metric facility location problems
SIAM JOURNAL ON COMPUTING
2006; 36 (2): 411-432
View details for DOI 10.1137/S0097539703435716
View details for Web of Science ID 000240043700006
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Leontief Economies Encode Nonzero Sum Two-Player Games
17th ACM-SIAM Symposium on Discrete Algorithms
SIAM. 2006: 659–667
View details for Web of Science ID 000281596300072
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A new complexity result on solving the Markov decision problem
MATHEMATICS OF OPERATIONS RESEARCH
2005; 30 (3): 733-749
View details for DOI 10.1287/moor.1050.0149
View details for Web of Science ID 000231792300011
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A multiexchange local search algorithm for the capacitated facility location problem
MATHEMATICS OF OPERATIONS RESEARCH
2005; 30 (2): 389-403
View details for DOI 10.1287/moor.1040.0125
View details for Web of Science ID 000230035200007
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On solving univariate sparse polynomials in logarithmic time
Conference on Foundations of Computational Mathematics (FoCM)
ACADEMIC PRESS INC ELSEVIER SCIENCE. 2005: 87–110
View details for DOI 10.1016/j.jco.2004.03.004
View details for Web of Science ID 000226701700005
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On solving coverage problems in a wireless sensor network using Voronoi diagrams
1st International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2005: 584–593
View details for Web of Science ID 000234851600058
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Computing the Arrow-Debreu competitive market equilibrium and its extensions
1st International Conference on Algorithmic Applications in Management
SPRINGER-VERLAG BERLIN. 2005: 3–5
View details for Web of Science ID 000230475100002
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Semidefinite programming algorithms for sensor network localization using angle information
39th Asilomar Conference on Signals, Systems and Computers
IEEE. 2005: 220–224
View details for Web of Science ID 000238142000040
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On approximating complex quadratic optimization problems via semidefinite programming relaxations
11th International Integer Programming and Combinatorial Optimization Conference
SPRINGER-VERLAG BERLIN. 2005: 125–135
View details for Web of Science ID 000230361400010
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Theory of Semidefinite Programming for Sensor Network Localization
16th Annual ACM-SIAM Symposium on Discrete Algorithms
SIAM. 2005: 405–414
View details for Web of Science ID 000281595800046
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Exchange market equilibria with Leontief's utility: Freedom of pricing leads to rationality
1st International Workshop on Internet and Network Economics
SPRINGER-VERLAG BERLIN. 2005: 14–23
View details for Web of Science ID 000234851600003
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Improved approximations for max set splitting and max NAE SAT
DISCRETE APPLIED MATHEMATICS
2004; 142 (1-3): 133-149
View details for DOI 10.1016/j.dam.2002.07.001
View details for Web of Science ID 000223098000011
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A multi-exchange local search algorithm for the capacitated facility location problem - (Extended abstract)
10th International Integer Programming and Combinatorial Optimization Conference
SPRINGER-VERLAG BERLIN. 2004: 219–233
View details for Web of Science ID 000222230000017
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Improved combinatorial approximation algorithms for the k-level facility location problem
SIAM JOURNAL ON DISCRETE MATHEMATICS
2004; 18 (1): 207-217
View details for DOI 10.1137/S0895480102417215
View details for Web of Science ID 000224348700015
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Semidefinite programming for ad hoc wireless sensor network localization
3rd International Symposium on Information Processing in Sensor Networks
ASSOC COMPUTING MACHINERY. 2004: 46–54
View details for Web of Science ID 000222055900006
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Approximating the 2-catalog segmentation problem using semidefinite programming relaxations
1st International Conference on Optimization Methods and Software (OMS2002)
TAYLOR & FRANCIS LTD. 2003: 705–19
View details for DOI 10.1080/10556780310001634082
View details for Web of Science ID 000187296300007
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An approximation algorithm for scheduling two parallel machines with capacity constraints
DISCRETE APPLIED MATHEMATICS
2003; 130 (3): 449-467
View details for DOI 10.1016/S0166-218X(02)00601-7
View details for Web of Science ID 000185241300006
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An improved algorithm for approximating the radii of point sets
6th Int Workshop on Approximation Algorithms for Combinatorial Optimization Problems/7th Int Workshop on Randomization and Approximation Techniques in Computer Science
SPRINGER-VERLAG BERLIN. 2003: 178–187
View details for Web of Science ID 000185994700016
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Improved combinatorial approximation algorithms for the k-level facility location problem
30th International Colloquium on Automata, Languages and Programming (ICALP 2003)
SPRINGER-VERLAG BERLIN. 2003: 145–156
View details for Web of Science ID 000185145700013
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New results on quadratic minimization
SIAM JOURNAL ON OPTIMIZATION
2003; 14 (1): 245-267
View details for DOI 10.1137/S105262340139001X
View details for Web of Science ID 000185130700010
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A 2-approximation algorithm for the soft-capacitated facility location problem
6th Int Workshop on Approximation Algorithms for Combinatorial Optimization Problems/7th Int Workshop on Randomization and Approximation Techniques in Computer Science
SPRINGER-VERLAG BERLIN. 2003: 129–140
View details for Web of Science ID 000185994700012
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A note on the maximization version of the multi-level facility location problem
OPERATIONS RESEARCH LETTERS
2002; 30 (5): 333-335
View details for Web of Science ID 000178894600007
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An improved rounding method and semidefinite programming relaxation for graph partition
17th International Symposium of the Mathematical-Programming-Society
SPRINGER. 2002: 509–35
View details for DOI 10.1007/s101070100288
View details for Web of Science ID 000176303700007
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Improved approximation algorithms for metric facility location problems
5th International Workshop on Approximation Algorithms for Combinatorial Optimization
SPRINGER-VERLAG BERLIN. 2002: 229–242
View details for Web of Science ID 000187294200020
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Approximating maximum stable set and minimum graph coloring problems with the positive semidefinite relaxation
International Conference on Complementarity 99 (ICCP99)
SPRINGER. 2001: 1–17
View details for Web of Science ID 000168052500001
- Blind Channel Equalization and Approximation Algorithms IEEE Trans. on Signal Processing 2001; 49 (11): 2823-2831
- A .699-approximation algorithm for Max-Bisection Mathematical Programming 2001; 90: 101-111
- On smoothing methods for the P0 matrix linear complementarity problem SIAM J. Optimization 2001; 11: 341-363
- An efficient algorithm for minimizing a sum of P-norms SIAM J. Optimization 2000; 10: 551-579
- A simplification to ``A Primal-Dual Interior Point Method Whose Running Time Depends Only on the Constraint Matrix'' High Performance Optimization, Applied Optimization 33 edited by Zhang, et al, S. 2000: 233–243
- Application of Semidefinite Programming to Circuit Partitioning Approximation and Complexity in Numerical Optimization edited by Pardalos, P. Kluwer Academics Publishers. 2000: 130–136
- Convergence results of analytic center estimator Analytic center approach to bounded error parameter IEEE Transactions on Automatic Control 2000
- Solving large-scale sparse semidefinite programs for combinatorial optimization SIAM J. Optimization 2000; 10: 443-461
- Probabilistic Analysis of an Infeasible Primal--Dual Algorithm for Linear Programming Mathematics of Operations Research 1999; 24: 176-192
- On a homogeneous algorithm for the monotone complementarity problem Mathematical Programming 1999; 84: 375-400
- Bounded Error Parameter Estimation: A Sequential Analytic Center Approach IEEE Transactions on Automatic Control 1999; 6 (44): 1107-1117
- On Homotopy-Smoothing Methods for Variational Inequalities SIAM J. Control & Optimization 1999; 37: 589-616
- Infeasible-start primal-dual methods and infeasibility detectors for nonlinear programming problems Mathematical Programming 1999; 84: 227-267
- Constrained Logarithmic Least Squares in Parameter Estimation IEEE Transactions on Automatic Control 1999; 1 (44): 182-185
- A computational study of the homogeneous algorithm for large-scale convex optimization Computational Optimization and Applications 1998; 10: 243-269
- Semidefinite Relaxations, Multivariate Normal Distributions, and Order Statistics Handbook of Combinatorial Optimization edited by Du, D., Z., Pardalos, P.M. Kluwer Academic Publishers. 1998: 1–19
- On the complexity of approximating a KKT point of quadratic programming Mathematical Programming 1998; 80: 195-212
- Approximation algorithms for quadratic programming Journal of Combinatorial Optimization 1998; 1 (2): 29-50
- Approximate Farkas lemmas and stopping rules for iterative infeasible-point algorithms for linear programming Mathematical Programming 1998; 81: 1-22
- An infeasible interior-point algorithm for solving primal and dual geometric programs Mathematical Programming 1997; 76: 155-182
- On a homogeneous algorithm for a monotone complementarity problem with nonlinear equality constraints Complementarity and variational Problems: State of the art edited by Ferris, Michael, C., Pang, J. SIAM. 1997: 1–11
- Improved complexity using higher-order correctors for primal-dual Dikin affine scaling Mathematical Programming 1997; 76: 117-130
- Complexity analysis of the analytic center cutting plane method that uses multiple cuts Mathematical Programming 1997; 78: 85-104
- On homogeneous and self-dual algorithm for LCP Mathematical Programming 1997; 76: 211-222
- Efficient algorithms for minimizing a sum of Euclidean norms with applications SIAM J. Optimization 1997; 7: 1017-1036
- A primal-dual interior-point method whose running time depends only on the constraint matrix Mathematical Programming 1996; 74: 79-120
- How partial knowledge helps to solve linear programs Journal of Complexity 1996; 12: 480-491
- Complexity analysis of an interior-point cutting plane method for convex feasibility problem SIAM J. Optimization 1996; 6: 638-652
- Combining interior-point and pivoting algorithms for linear programming Management Science 1996; 42: 1719-1731
- A lower bound on the number of iterations of long-step and polynomial interior-point linear programming algorithms Annals of Operations Research 1996; 62: 233-252
- A asymptotical O(√nL) -iteration path-following linear programming algorithm that uses long steps SIAM J. Optimization 1996; 6: 570-586
- Interior-point methods for nonlinear complementarity problem Journal of Optimization Theory and Application 1996; 68
- Identifying an optimal basis in linear programming Annals of Operations Research 1996; 62: 565-572
- A simplified homogeneous and self-dual linear programming algorithm and its implementation Annals of Operations Research 1996; 62: 151-172
- A surface of analytic centers and infeasible-interior-point algorithms for linear programming Mathematics of Operations Research 1995; 20: 135-162
- On the von Neumann economic growth problem Mathematics Operations Research 1995; 20: 617-633
- Condition numbers for polyhedra with real number data Operations Research Letters 1995; 17: 209-214
- A generalized homogeneous and self-dual linear programming algorithm Operations Research Letters 1995; 17
- On the convergence of the iteration sequence in primal-dual interior-point methods Mathematical Programming 1995; 68: 141-154
- The optimal choice of inputs under time of use pricing, fixed proportions technology and adjustment costs: an application to industrial firms Management Sciences 1995; 41: 1679-1692
- A convergent algorithm for quantile regression with smoothing splines Computational Statistics & Data Analysis 1995; 19: 613-630
- Specially structured uncapacitated facility location problems Operations Research 1995; 43: 661-669
- Combining binary search and Newton's method to compute real roots for a class of real functions Journal of Complexity 1994; 10: 271-280
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ON THE COMPLEXITY OF A COLUMN GENERATION ALGORITHM FOR CONVEX OR QUASI-CONVEX FEASIBILITY PROBLEMS
Conference on Large Scale Optimization
KLUWER ACADEMIC PUBL. 1994: 182–191
View details for Web of Science ID A1994BA62H00010
- A genuine quadratically convergent polynomial interior point algorithm for linear programming Advances in Optimization and Approximation edited by Du, D., Sun, J. Kluwer Academic Publishers, Boston. 1994: 1
- On the complexity of a column generation algorithm for convex or quasiconvex feasibility problems Large Scale Optimization: State of the Art edited by Hager, W., Hearn, D., Pardalos, P. Kluwer Academic Publishers, Boston. 1994: 182–191
- A complexity analysis for interior-point algorithms based on Karmarkar's potential functions SIAM J. on Optimization 1994; 4: 512-520
- Toward probabilistic analysis of interior-point algorithms for linear programming Mathematics of Operations Research 1994; 19: 38-52
- An $O(\sqrt{n}L)$-iteration homogeneous and self-dual linear programming algorithm Mathematics of Operations Research 1994; 19: 53-67
- An accelerated interior-point method whose running time depends only on $A$ 1994
- A decomposition variant of the potential reduction algorithm for linear programming Management Science 1993; 39: 757-776
- Average performance of a self-dual interior-point algorithm for linear programming Complexity in Numerical Optimization edited by Pardalos, P. World Scientific, New Jersey. 1993: 1–15
- Translation cuts for convex minimization Complexity in Numerical Optimization edited by Pardalos, P. World Scientific, New Jersey. 1993: 57–73
- Solutions of $P_0$-matrix linear complementarity problems SIAM J. on Matrix Anal. Appl. 1993; 14: 1048-1060
- Near-boundary behavior of the primal-dual potential reduction algorithm for linear programming Mathematical Programming 1993; 58: 243-255
- Minimal adjustment costs, factor demands, and seasonal time-of-use electricity rates Resource and Energy Economics 1993; 15: 313-335
- An extension of the potential reduction algorithm for solving LCP with priority goals Linear Algebra and its Applications 1993; 193: 35-50
- A quadratically convergent polynomial interior-point algorithm for solving entropy optimization problems SIAM J. on Optimization 1993; 3: 843-860
- On quadratic and $O(\sqrt{n}L)$ convergence of a predictor- corrector algorithm for LCP Mathematical Programming 1993; 62: 537-552
- On finding an interior point on the optimal face of linear programs Mathematical Programming 1993; 62: 497-516
- On adaptive-step primal-dual interior-point algorithms for linear programming Mathematics of Operations Research 1993; 18: 964-981
- A quadratically convergent $O(\sqrt{n}L)$-iteration algorithm for linear programming Mathematical Programming 1993; 59: 151-162
- A fully polynomial-time approximation algorithm for computing a stationary point of the general LCP Mathematics of Operations Research 1993; 18: 334-345
- Convergence behavior of some interior-point algorithms Mathematical Programming 1993; 60: 215-228
- Extensions of the potential reduction algorithm for linear programming Journal of Optimization Theory and Applications 1992; 193: 35-50
- On the Q-order of convergence of interior-point algorithms for linear programming edited by Fang, W. 1992
- A further result on potential reduction algorithm for the P-matrix linear complementarity problem Advances in Optimization and Parallel Computing, edited by Pardalos, P. North-Holland, NY. 1992: 1
- A new complexity result on minimization of a quadratic function with a sphere constraint Recent Advances in Global Optimization edited by Floudas, C., Pardalos, P. Princeton University Press, NJ. 1992: 1
- On affine scaling algorithms for nonconvex quadratic programming Mathematical Programming 1992; 56: 285-300
- Comparative analysis of affine scaling algorithms for linear programming Mathematical Programming 1992; 52: 405-414
- A potential reduction algorithm allowing column generation SIAM J. on Optimization 1992; 2: 7-20
- On the finite convergence of interior-point algorithms for linear programming Mathematical Programming 1992; 57: 325-335
- Implementation of interior-point algorithms for some entropy optimization problems Optimization Methods and Software 1992; 1: 71-80
- An interior point potential reduction algorithm for the linear complementarity problem Mathematical Programming 1992; 54: 267-279
- A class of LCPs solvable in polynomial time Linear Algebra and its Applications 1991; 152: 3-17
- Interior-point algorithms for quadratic programming Recent Developments in Mathematical Programming edited by Kumar, S. Gordon \& Breach Scientific Publishers, Philadelphia. 1991: 1
- On some efficient interior point methods for nonlinear convex programming Linear Algebra and its Applications 1991; 152: 169-189
- Interior-point algorithms for solving nonlinear optimization problems COAL Newsletter 1991; 19: 45-54
- Convergence behavior of Karmarkar's projective algorithm for solving a simple linear program Operations Research Letters 1991; 10: 389-393
- An $O(n^3L)$ potential reduction algorithm for linear programming Mathematical Programming 1991; 50: 239-258
- Algorithms for the solution of quadratic knapsack problems Linear Algebra and its Applications 1991; 152: 69-91
- A class of projective transformations for linear programming SIAM J. on Computing 1990; 19: 457-466
- Computational aspects of an interior point algorithm for quadratic programming problems with box constraints Large-Scale Numerical Optimization edited by Coleman, T., F., Li, Y. SIAM, Philadelphia. 1990: 1
- Interior-point algorithms for global optimization Annals of Operations Research 1990; 25: 59-74
- Containing and shrinking ellipsoids in the path-following algorithm Mathematical Programming 1990; 47: 1-9
- A centered projective algorithm for linear programming Mathematics of Operations Research 1990; 15: 508-529
- A ``build-down'' scheme for linear programming Mathematical Programming 1990; 46: 61-72
- Recovering optimal basic variables in Karmarkar's polynomial algorithm for linear programming Mathematics of Operations Research 1990; 15: 564-571
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AN EXTENSION OF KARMARKAR PROJECTIVE ALGORITHM FOR CONVEX QUADRATIC-PROGRAMMING
MATHEMATICAL PROGRAMMING
1989; 44 (2): 157-179
View details for Web of Science ID A1989AE14900003
- An extension of Karmarkar's projective algorithm for convex quadratic programming Mathematical Programming 1989; 44: 157-179
- Eliminating columns in the simplex method for linear programming Journal of Optimization Theory and Applications 1989; 63: 103-111
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RECOVERING OPTIMAL DUAL SOLUTIONS IN KARMARKARS POLYNOMIAL ALGORITHM FOR LINEAR-PROGRAMMING
MATHEMATICAL PROGRAMMING
1987; 39 (3): 305-317
View details for Web of Science ID A1987L163200006
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KARMARKAR ALGORITHM AND THE ELLIPSOID METHOD
OPERATIONS RESEARCH LETTERS
1987; 6 (4): 177-182
View details for Web of Science ID A1987K479100005
- Recovering optimal dual solutions in Karmarkar's polynomial algorithm for linear programming Mathematical Programming 1987; 39: 305-317
- A conclusion on `missing number' in ergodic exponents of $s\times s$ stochastic matrices Journal of Huazhong University of Science and Technology 1983; 2
- Directed graphs, linear Diophantine equations, and ergodic problems of stochastic matrices, English Edit. Journal of Huazhong University of Science and Technology 1982; 2