Yinyu Ye

All Publications

• A gradient descent akin method for constrained optimization: algorithms and applications OPTIMIZATION METHODS & SOFTWARE Chen, L., Bletzinger, K., Gauger, N. R., Ye, Y. 2024

  View details for DOI 10.1080/10556788.2023.2285450

  View details for Web of Science ID 001143083200001

• Worst-Case Iteration Bounds for Log Barrier Methods on Problems with Nonconvex Constraints MATHEMATICS OF OPERATIONS RESEARCH Hinder, O., Ye, Y. 2023

  View details for DOI 10.1287/moor.2020.0274

  View details for Web of Science ID 001113185300001

• Optimization of Asset Allocation and Liquidation Time in Investment Decisions with VaR as a Risk Measure COMPUTATIONAL ECONOMICS Xu, C., Ye, Y. 2023

  View details for DOI 10.1007/s10614-023-10451-x

  View details for Web of Science ID 001049987800001

• Fisher markets with linear constraints: Equilibrium properties and efficient distributed algorithms GAMES AND ECONOMIC BEHAVIOR Jalota, D., Pavone, M., Qi, Q., Ye, Y. 2023; 141: 223-260

  View details for DOI 10.1016/j.geb.2023.06.007

  View details for Web of Science ID 001039441900001

• Simple and fast algorithm for binary integer and online linear programming MATHEMATICAL PROGRAMMING Li, X., Sun, C., Ye, Y. 2022

  View details for DOI 10.1007/s10107-022-01880-x

  View details for Web of Science ID 000847620700001

• An Improved Analysis of LP-Based Control for Revenue Management OPERATIONS RESEARCH Chen, G., Li, X., Ye, Y. 2022

  View details for DOI 10.1287/opre.2022.2358

  View details for Web of Science ID 000841481500001

• Optimization and Operations Research in Mitigation of a Pandemic JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF CHINA Chen, C., Du, Y., Ge, D., Lei, L., Ye, Y. 2022; 10 (2): 289-304

  View details for DOI 10.1007/s40305-022-00391-y

  View details for Web of Science ID 000793649600001

• High-Dimensional Learning Under Approximate Sparsity with Applications to Nonsmooth Estimation and Regularized Neural Networks OPERATIONS RESEARCH Liu, H., Ye, Y., Lee, H. 2022

  View details for DOI 10.1287/opre.2021.2217

  View details for Web of Science ID 000803709700001

• Distributed Stochastic Optimization with Large Delays MATHEMATICS OF OPERATIONS RESEARCH Zhou, Z., Mertikopoulos, P., Bambos, N., Glynn, P., Ye, Y. 2021

  View details for DOI 10.1287/moor.2021.1200

  View details for Web of Science ID 000731960500001

• Online Linear Programming: Dual Convergence, New Algorithms, and Regret Bounds OPERATIONS RESEARCH Li, X., Ye, Y. 2021

  View details for DOI 10.1287/opre.2021.2164

  View details for Web of Science ID 000731969400001

• Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs (vol 181, pg 1, 2020) MATHEMATICAL PROGRAMMING Burer, S., Ye, Y. 2021

  View details for DOI 10.1007/s10107-021-01684-5

  View details for Web of Science ID 000670874000001

• Variance reduced value iteration and faster algorithms for solving Markov decision processes NAVAL RESEARCH LOGISTICS Sidford, A., Wang, M., Wu, X., Ye, Y. 2021

  View details for DOI 10.1002/nav.21992

  View details for Web of Science ID 000642314100001

• The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks Li, X., Sun, C., Ye, Y., Meila, M., Zhang, T. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2021

  View details for Web of Science ID 000683104606047

• A Mathematical Programming Formulation for Optimal Load Shifting of Electricity Demand for the Smart Grid IEEE TRANSACTIONS ON BIG DATA Hu, R., Skorupski, R., Entriken, R., Ye, Y. 2020; 6 (4): 638–51

  View details for DOI 10.1109/TBDATA.2016.2639528

  View details for Web of Science ID 000591809700003

• An ADMM-based interior-point method for large-scale linear programming OPTIMIZATION METHODS & SOFTWARE Lin, T., Ma, S., Ye, Y., Zhang, S. 2020

  View details for DOI 10.1080/10556788.2020.1821200

  View details for Web of Science ID 000572518800001

• Managing randomization in the multi-block alternating direction method of multipliers for quadratic optimization MATHEMATICAL PROGRAMMING COMPUTATION Mihic, K., Zhu, M., Ye, Y. 2020

  View details for DOI 10.1007/s12532-020-00192-5

  View details for Web of Science ID 000572298400001

• On the complexity of an expanded Tarski's fixed point problem under the componentwise ordering (vol 732, pg 26, 2018) THEORETICAL COMPUTER SCIENCE Dang, C., Ye, Y. 2020; 817: 80

  View details for DOI 10.1016/j.tcs.2019.03.014

  View details for Web of Science ID 000524287900009

• Exact semidefinite formulations for a class of (random and non-random) nonconvex quadratic programs MATHEMATICAL PROGRAMMING Burer, S., Ye, Y. 2020; 181 (1): 1–17

  View details for DOI 10.1007/s10107-019-01367-2

  View details for Web of Science ID 000531046500001

• On the Efficiency of Random Permutation for ADMM and Coordinate Descent MATHEMATICS OF OPERATIONS RESEARCH Sun, R., Luo, Z., Ye, Y. 2020; 45 (1): 233–71

  View details for DOI 10.1287/moor.2019.0990

  View details for Web of Science ID 000512979600011

• MULTILEVEL MONTE CARLO SAMPLING ON HETEROGENEOUS COMPUTER ARCHITECTURES INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION Adcock, C., Ye, Y., Jofre, L., Laccarino, G. 2020; 10 (6): 575–94

  View details for DOI 10.1615/Int.J.UncertaintyQuantification.2020033179

  View details for Web of Science ID 000599583800005

• Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity Sidford, A., Wang, M., Yang, L. F., Ye, Y., Chiappa, S., Calandra, R. ADDISON-WESLEY PUBL CO. 2020

  View details for Web of Science ID 000559931303021

• On the behavior of Lagrange multipliers in convex and nonconvex infeasible interior point methods MATHEMATICAL PROGRAMMING Haeser, G., Hinder, O., Ye, Y. 2019

  View details for DOI 10.1007/s10107-019-01454-4

  View details for Web of Science ID 000574702400001

• Towards solving 2-TBSG efficiently OPTIMIZATION METHODS & SOFTWARE Jia, Z., Wen, Z., Ye, Y. 2019

  View details for DOI 10.1080/10556788.2019.1695131

  View details for Web of Science ID 000501692900001

• Optimality condition and complexity analysis for linearly-constrained optimization without differentiability on the boundary MATHEMATICAL PROGRAMMING Haeser, G., Liu, H., Ye, Y. 2019; 178 (1-2): 263–99

  View details for DOI 10.1007/s10107-018-1290-4

  View details for Web of Science ID 000495020200007

• Sample Average Approximation with Sparsity-Inducing Penalty for High-Dimensional Stochastic Programming. Mathematical programming Liu, H., Wang, X., Yao, T., Li, R., Ye, Y. 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

• Worst-case complexity of cyclic coordinate descent: O(n(2)) gap with randomized version MATHEMATICAL PROGRAMMING Sun, R., Ye, Y. 2019

  View details for DOI 10.1007/s10107-019-01437-5

  View details for Web of Science ID 000492250700001

• Approximation Hardness for A Class of Sparse Optimization Problems JOURNAL OF MACHINE LEARNING RESEARCH Chen, Y., Ye, Y., Wang, M. 2019; 20

  View details for Web of Science ID 000464271900001

• Interior-point Methods Strike Back: Solving the Wasserstein Barycenter Problem Ge, D., Wang, H., Xiong, Z., Ye, Y., 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 000534424306085

• Extended ADMM and BCD for nonseparable convex minimization models with quadratic coupling terms: convergence analysis and insights MATHEMATICAL PROGRAMMING Chen, C., Li, M., Liu, X., Ye, Y. 2019; 173 (1-2): 37–77

  View details for DOI 10.1007/s10107-017-1205-9

  View details for Web of Science ID 000456970900002

• On the complexity of an expanded Tarski's fixed point problem under the componentwise ordering THEORETICAL COMPUTER SCIENCE Dang, C., Ye, Y. 2018; 732: 26–45

  View details for DOI 10.1016/jscs.2018.04.021

  View details for Web of Science ID 000433999200003

• Learning in Games with Lossy Feedback Zhou, Z., Mertikopoulos, P., Athey, S., Bambos, N., Glynn, P., Ye, Y., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018

  View details for Web of Science ID 000461823305017

• Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes Sidford, A., Wang, M., Wu, X., Ye, Y., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 770–87

  View details for Web of Science ID 000483921200051

• Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model Sidford, A., Wang, M., Wu, X., Yang, L. F., Ye, Y., Bengio, S., Wallach, H., Larochelle, H., Grauman, K., CesaBianchi, N., Garnett, R. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2018

  View details for Web of Science ID 000461823305022

• ON DOUBLY POSITIVE SEMIDEFINITE PROGRAMMING RELAXATIONS Fu, T., Ge, D., Ye, Y. GLOBAL SCIENCE PRESS. 2018: 391–403

  View details for DOI 10.4208/jcm.1708-m2017-0130

  View details for Web of Science ID 000455995700005

• Special issue on "Modern Optimization and Applications" Preface JOURNAL OF COMPUTATIONAL MATHEMATICS Chen, X., Dai, Y., Richtarik, P., Ye, Y. 2018; 36 (3): I-II

  View details for Web of Science ID 000455995700001

• A computation study on an integrated alternating direction method of multipliers for large scale optimization OPTIMIZATION LETTERS Zarepisheh, M., Xing, L., Ye, Y. 2018; 12 (1): 3–15

  View details for DOI 10.1007/s11590-017-1116-y

  View details for Web of Science ID 000419552800002

• Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions. Mathematical programming Liu, H., Yao, T., Li, R., Ye, Y. 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

• On a New SDP-SOCP Method for Acoustic Source Localization Problem ACM TRANSACTIONS ON SENSOR NETWORKS Gao, M., Yiu, K. C., Nordholm, S., Ye, Y. 2016; 12 (4)

  View details for DOI 10.1145/2968449

  View details for Web of Science ID 000388853800011

• Hidden-City Ticketing: The Cause and Impact TRANSPORTATION SCIENCE Wang, Z., Ye, Y. 2016; 50 (1): 288-305

  View details for DOI 10.1287/trsc.2015.0587

  View details for Web of Science ID 000375655400019

• The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent MATHEMATICAL PROGRAMMING Chen, C., He, B., Ye, Y., Yuan, X. 2016; 155 (1-2): 57-79

  View details for DOI 10.1007/s10107-014-0826-5

  View details for Web of Science ID 000367695200002

• The Simplex Method is Strongly Polynomial for Deterministic Markov Decision Processes MATHEMATICS OF OPERATIONS RESEARCH Post, I., Ye, Y. 2015; 40 (4): 859-868

  View details for DOI 10.1287/moor.2014.0699

  View details for Web of Science ID 000367895700004

• A fixed point iterative approach to integer programming and its distributed computation FIXED POINT THEORY AND APPLICATIONS Dang, C., Ye, Y. 2015

  View details for DOI 10.1186/s13663-015-0429-8

  View details for Web of Science ID 000366020200004

• A homogeneous interior-point algorithm for nonsymmetric convex conic optimization MATHEMATICAL PROGRAMMING Skajaa, A., Ye, Y. 2015; 150 (2): 391-422

  View details for DOI 10.1007/s10107-014-0773-1

  View details for Web of Science ID 000351522700007

• Simultaneous beam sampling and aperture shape optimization for SPORT. Medical physics Zarepisheh, M., Li, R., Ye, Y., Xing, L. 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

• Complexity analysis of interior point algorithms for non-Lipschitz and nonconvex minimization MATHEMATICAL PROGRAMMING Bian, W., Chen, X., Ye, Y. 2015; 149 (1-2): 301-327

  View details for DOI 10.1007/s10107-014-0753-5

  View details for Web of Science ID 000347830300011

• The Value of Stochastic Modeling in Two-Stage Stochastic Programs with Cost Uncertainty OPERATIONS RESEARCH Delage, E., Arroyo, S., Ye, Y. 2014; 62 (6): 1377-1393

  View details for DOI 10.1287/opre.2014.1318

  View details for Web of Science ID 000346153600012

• Space tensor conic programming COMPUTATIONAL OPTIMIZATION AND APPLICATIONS Qi, L., Ye, Y. 2014; 59 (1-2): 307-319

  View details for DOI 10.1007/s10589-013-9577-0

  View details for Web of Science ID 000341495800016

• A Levenberg-Marquardt method with approximate projections COMPUTATIONAL OPTIMIZATION AND APPLICATIONS Behling, R., Fischer, A., Herrich, M., Iusem, A., Ye, Y. 2014; 59 (1-2): 5-26

  View details for DOI 10.1007/s10589-013-9573-4

  View details for Web of Science ID 000341495800002

• Waterflood management using two-stage optimization with streamline simulation COMPUTATIONAL GEOSCIENCES Wen, T., Thiele, M. R., Ciaurri, D. E., Aziz, K., Ye, Y. 2014; 18 (3-4): 483-504

  View details for DOI 10.1007/s10596-014-9404-4

  View details for Web of Science ID 000341492200015

• A Dynamic Near-Optimal Algorithm for Online Linear Programming OPERATIONS RESEARCH Agrawal, S., Wang, Z., Ye, Y. 2014; 62 (4): 876-890

  View details for DOI 10.1287/opre.2014.1289

  View details for Web of Science ID 000343248400011

• Close the Gaps: A Learning-While-Doing Algorithm for Single-Product Revenue Management Problems OPERATIONS RESEARCH Wang, Z., Deng, S., Ye, Y. 2014; 62 (2): 318-331

  View details for DOI 10.1287/opre.2013.1245

  View details for Web of Science ID 000335394200007

• Complexity of unconstrained minimization MATHEMATICAL PROGRAMMING Chen, X., Ge, D., Wang, Z., Ye, Y. 2014; 143 (1-2): 371-383

  View details for DOI 10.1007/s10107-012-0613-0

  View details for Web of Science ID 000330038300014

• Analytical Results and Efficient Algorithm for Optimal Portfolio Deleveraging with Market Impact OPERATIONS RESEARCH Chen, J., Feng, L., Peng, J., Ye, Y. 2014; 62 (1): 195-206

  View details for DOI 10.1287/opre.2013.1222

  View details for Web of Science ID 000332013300013

• A Dynamic Algorithm for Facilitated Charging of Plug-In Electric Vehicles IEEE TRANSACTIONS ON SMART GRID Taheri, N., Entriken, R., Ye, Y. 2013; 4 (4): 1772-1779

  View details for DOI 10.1109/TSG.2012.2233768

  View details for Web of Science ID 000328064100004

• Newsvendor optimization with limited distribution information OPTIMIZATION METHODS & SOFTWARE Zhu, Z., Zhang, J., Ye, Y. 2013; 28 (3): 640-667

  View details for DOI 10.1080/10556788.2013.768994

  View details for Web of Science ID 000320093700016

• On stress matrices of (d+1)-lateration frameworks in general position MATHEMATICAL PROGRAMMING Alfakih, A. Y., Taheri, N., Ye, Y. 2013; 137 (1-2): 1-17

  View details for DOI 10.1007/s10107-011-0480-0

  View details for Web of Science ID 000313797100001

• On affine motions and bar frameworks in general position LINEAR ALGEBRA AND ITS APPLICATIONS Alfakih, A. Y., Ye, Y. 2013; 438 (1): 31-36

  View details for DOI 10.1016/j.laa.2012.08.031

  View details for Web of Science ID 000312682900004

• Beyond Convex Relaxation: A Polynomial-Time Non-Convex Optimization Approach to Network Localization 32nd IEEE INFOCOM Conference Ji, S., Sze, K., Zhou, Z., So, A. M., Ye, Y. IEEE. 2013: 2499–2507

  View details for Web of Science ID 000326335202070

• THE CUBIC SPHERICAL OPTIMIZATION PROBLEMS MATHEMATICS OF COMPUTATION Zhang, X., Qi, L., Ye, Y. 2012; 81 (279): 1513-1525

  View details for Web of Science ID 000305099000011

• A FPTAS for computing a symmetric Leontief competitive economy equilibrium MATHEMATICAL PROGRAMMING Zhu, Z., Dang, C., Ye, Y. 2012; 131 (1-2): 113-129

  View details for DOI 10.1007/s10107-010-0348-8

  View details for Web of Science ID 000299180900006

• A variational principle for computing nonequilibrium fluxes and potentials in genome-scale biochemical networks JOURNAL OF THEORETICAL BIOLOGY Fleming, R. M., MAES, C. M., Saunders, M. A., Ye, Y., Palsson, B. O. 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

• Price of Correlations in Stochastic Optimization OPERATIONS RESEARCH Agrawal, S., Ding, Y., Saberi, A., Ye, Y. 2012; 60 (1): 150-162

  View details for DOI 10.1287/opre.1110.1011

  View details for Web of Science ID 000302113900013

• Geometric rounding: a dependent randomized rounding scheme JOURNAL OF COMBINATORIAL OPTIMIZATION Ge, D., He, S., Ye, Y., Zhang, J. 2011; 22 (4): 699-725

  View details for DOI 10.1007/s10878-010-9320-z

  View details for Web of Science ID 000296520200017

• The Simplex and Policy-Iteration Methods Are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate MATHEMATICS OF OPERATIONS RESEARCH Ye, Y. 2011; 36 (4): 593-603

  View details for DOI 10.1287/moor.1110.0516

  View details for Web of Science ID 000296977700001

• An interior-point path-following algorithm for computing a Leontief economy equilibrium COMPUTATIONAL OPTIMIZATION AND APPLICATIONS Dang, C., Ye, Y., Zhu, Z. 2011; 50 (2): 223-236

  View details for DOI 10.1007/s10589-010-9332-8

  View details for Web of Science ID 000295574600003

• A note on the complexity of L-p minimization MATHEMATICAL PROGRAMMING Ge, D., Jiang, X., Ye, Y. 2011; 129 (2): 285-299

  View details for DOI 10.1007/s10107-011-0470-2

  View details for Web of Science ID 000295785000006

• An Optimization Approach to Improving Collections of Shape Maps COMPUTER GRAPHICS FORUM Andy Nguyen, A., Ben-Chen, M., Welnicka, K., Ye, Y., Guibas, L. 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

• A Unified Framework for Dynamic Prediction Market Design OPERATIONS RESEARCH Agrawal, S., Delage, E., Peters, M., Wang, Z., Ye, Y. 2011; 59 (3): 550-568

  View details for DOI 10.1287/opre.1110.0922

  View details for Web of Science ID 000292639000003

• Statistical ranking and combinatorial Hodge theory MATHEMATICAL PROGRAMMING Jiang, X., Lim, L., Yao, Y., Ye, Y. 2011; 127 (1): 203-244

  View details for DOI 10.1007/s10107-010-0419-x

  View details for Web of Science ID 000288371400009

• 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) Dang, C., Ye, Y. WORLD PUBLISHING CORPORATION. 2011: 258–263

  View details for Web of Science ID 000306631500031

• ON EQUILIBRIUM PRICING AS CONVEX OPTIMIZATION JOURNAL OF COMPUTATIONAL MATHEMATICS Chen, L., Ye, Y., Zhang, J. 2010; 28 (5): 569-578

  View details for DOI 10.4208/jcm.1003-m0001

  View details for Web of Science ID 000281879100001

• Semidefinite Relaxation of Quadratic Optimization Problems IEEE SIGNAL PROCESSING MAGAZINE Luo, Z., Ma, W., So, A. M., Ye, Y., Zhang, S. 2010; 27 (3): 20-34

  View details for DOI 10.1109/MSP.2010.936019

  View details for Web of Science ID 000276819100006

• Special Issue in Memory of Alexander Rubinov PACIFIC JOURNAL OF OPTIMIZATION Fukushima, M., Kelley, C. T., Qi, L., Sun, J., Ye, Y. 2010; 6 (2)

  View details for Web of Science ID 000278611300001

• Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems OPERATIONS RESEARCH Delage, E., Ye, Y. 2010; 58 (3): 595-612

  View details for DOI 10.1287/opre.1090.0741

  View details for Web of Science ID 000278912100006

• Dynamic Spectrum Management With the Competitive Market Model IEEE TRANSACTIONS ON SIGNAL PROCESSING Xie, Y., Armbruster, B., Ye, Y. 2010; 58 (4): 2442-2446

  View details for DOI 10.1109/TSP.2009.2039820

  View details for Web of Science ID 000275370800048

• A novel fluence map optimization model incorporating leaf sequencing constraints PHYSICS IN MEDICINE AND BIOLOGY Jin, R., Min, Z., Song, E., Liu, H., Ye, Y. 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

• UNIVERSAL RIGIDITY AND EDGE SPARSIFICATION FOR SENSOR NETWORK LOCALIZATION SIAM JOURNAL ON OPTIMIZATION Zhu, Z., So, A. M., Ye, Y. 2010; 20 (6): 3059-3081

  View details for DOI 10.1137/090772009

  View details for Web of Science ID 000285547100015

• LOWER BOUND THEORY OF NONZERO ENTRIES IN SOLUTIONS OF l(2)-l(p) MINIMIZATION SIAM JOURNAL ON SCIENTIFIC COMPUTING Chen, X., Xu, F., Ye, Y. 2010; 32 (5): 2832-2852

  View details for DOI 10.1137/090761471

  View details for Web of Science ID 000283293500030

• The Complexity of Determining the Uniqueness of Tarski's Fixed Point under the Lexicographic Ordering 6th International Workshop on Internet and Network Economics Dang, C., Ye, Y. SPRINGER-VERLAG BERLIN. 2010: 455–461

  View details for Web of Science ID 000290644400038

• Universal Rigidity: Towards Accurate and Efficient Localization of Wireless Networks Conference on IEEE INFOCOM Zhu, Z., So, A. M., Ye, Y. IEEE. 2010

  View details for Web of Science ID 000287416300158

• Correlation Robust Stochastic Optimization 21st Annual ACM/SIAM Symposium on Discrete Algorithms Agrawal, S., Ding, Y., Saberi, A., Ye, Y. SIAM. 2010: 1087–1096

  View details for Web of Science ID 000280699900088

• Finding Equitable Convex Partitions of Points in a Polygon Efficiently ACM TRANSACTIONS ON ALGORITHMS Carlsson, J. G., Armbruster, B., Ye, Y. 2010; 6 (4)

  View details for DOI 10.1145/1824777.1824792

  View details for Web of Science ID 000284382400016

• Stochastic Combinatorial Optimization with Controllable Risk Aversion Level MATHEMATICS OF OPERATIONS RESEARCH So, A. M., Zhang, J., Ye, Y. 2009; 34 (3): 522-537

  View details for DOI 10.1287/moor.1090.0390

  View details for Web of Science ID 000269484000002

• Conceptual formulation on four-dimensional inverse planning for intensity modulated radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Lee, L., Ma, Y., Ye, Y., Xing, L. 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

• An edge-reduction algorithm for the vertex cover problem OPERATIONS RESEARCH LETTERS Han, Q., Punnen, A. P., Ye, Y. 2009; 37 (3): 181-186

  View details for DOI 10.1016/j.orl.2009.01.010

  View details for Web of Science ID 000266360900009

• Budget Allocation in a Competitive Communication Spectrum Economy EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING Lin, M., Tsai, J., Ye, Y. 2009

  View details for DOI 10.1155/2009/963717

  View details for Web of Science ID 000266315900001

• A Unified Framework for Dynamic Pari-Mutuel Information Market Design 10th ACM Conference on Electronic Commerce (EC-2009) Agrawal, S., Delage, E., Peters, M., Wang, Z., Ye, Y. ASSOC COMPUTING MACHINERY. 2009: 255–264

  View details for Web of Science ID 000294744400030

• BIQUADRATIC OPTIMIZATION OVER UNIT SPHERES AND SEMIDEFINITE PROGRAMMING RELAXATIONS SIAM JOURNAL ON OPTIMIZATION Ling, C., Nie, J., Qi, L., Ye, Y. 2009; 20 (3): 1286-1310

  View details for DOI 10.1137/080729104

  View details for Web of Science ID 000277836500009

• Solving Min-Max Multi-Depot Vehicle Routing Problem Workshop on Global Optimization - Methods and Applications Carlsson, J., Ge, D., Subramaniam, A., Ye, Y. AMER MATHEMATICAL SOC. 2009: 31–46

  View details for Web of Science ID 000270995500003

• Using total-variation regularization for intensity modulated radiation therapy inverse planning with field-specific numbers of segments PHYSICS IN MEDICINE AND BIOLOGY Zhu, L., Lee, L., Ma, Y., Ye, Y., Mazzeo, R., Xing, L. 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

• The complexity of equilibria: Hardness results for economies via a correspondence with games Workshop on Excursions in Algoritmics Codenotti, B., Saberi, A., Varadarajan, K., Ye, Y. 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

• A Unified Theorem on SDP Rank Reduction MATHEMATICS OF OPERATIONS RESEARCH So, A. M., Ye, Y., Zhang, J. 2008; 33 (4): 910-920

  View details for DOI 10.1287/moor.1080.0326

  View details for Web of Science ID 000261150000009

• Preface ALGORITHMICA Deng, X., Ye, Y. 2008; 52 (1): 1-2

  View details for DOI 10.1007/s00453-007-9001-1

  View details for Web of Science ID 000258107400001

• 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

• A FPTAS for Computing a Symmetric Leontief Competitive Economy Equilibrium 4th International Workshop on Internet and Network Economics Zhu, Z., Dang, C., Ye, Y. SPRINGER-VERLAG BERLIN. 2008: 31–40

  View details for Web of Science ID 000262046200003

• Parimutuel Betting on Permutations 4th International Workshop on Internet and Network Economics Agrawal, S., Wang, Z., Ye, Y. SPRINGER-VERLAG BERLIN. 2008: 126–137

  View details for Web of Science ID 000262046200012

• A distributed SDP approach for large-scale noisy anchor-free graph realization with applications to molecular conformation SIAM JOURNAL ON SCIENTIFIC COMPUTING Biswas, P., Toh, K., Ye, Y. 2008; 30 (3): 1251-1277

  View details for DOI 10.1137/05062754X

  View details for Web of Science ID 000255500500007

• Algorithm 875: DSDP5 - Software for semidefinite programming ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE Benson, S. J., Ye, Y. 2008; 34 (3)

  View details for DOI 10.1145/1356052.1356057

  View details for Web of Science ID 000256338400005

• 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) Zhu, L., Ma, Y., Lee, L., Ye, Y., Mazzeo, R., Xing, L. ELSEVIER SCIENCE INC. 2008: S675–S675

  View details for Web of Science ID 000258805302411

• A path to the Arrow-Debreu competitive market equilibrium 5th Brazilian Workshop on Continuous Optimization Ye, Y. SPRINGER. 2008: 315–48

  View details for DOI 10.1007/s10107-006-0065-5

  View details for Web of Science ID 000247429500014

• Exchange market equilibria with Leontief's utility: Freedom of pricing leads to rationality 1st International Workshop on Internet and Network Economics Ye, Y. 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

• On approximating complex quadratic optimization problems via semidefinite programming relaxations 11th IPCO Conference So, A. M., Zhang, J., Ye, Y. SPRINGER. 2007: 93–110

  View details for DOI 10.1007/s10107-006-0064-6

  View details for Web of Science ID 000244889700006

• A ubiquitin ligase transfers preformed polyubiquitin chains from a conjugating enzyme to a substrate NATURE Li, W., Tu, D., Brunger, A. T., Ye, Y. 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

• Theory of semidefinite programming for sensor network localization 16th Annual ACM-SIAM Symposium on Discrete Algorithms So, A. M., Ye, Y. SPRINGER. 2007: 367–84

  View details for DOI 10.1007/s10107-006-0040-1

  View details for Web of Science ID 000243908500008

• Pari-mutuel markets: Mechanisms and performance 3rd International Workshop on Internet and Network Economics Peters, M., So, A. M., Ye, Y. SPRINGER-VERLAG BERLIN. 2007: 82–95

  View details for Web of Science ID 000252182500011

• Approximating the radii of point sets SIAM JOURNAL ON COMPUTING Varadarajan, K., Venkatesh, S., Ye, Y., Zhang, J. 2007; 36 (6): 1764-1776

  View details for DOI 10.1137/050627472

  View details for Web of Science ID 000246299400012

• Semidefinite programming approaches for sensor network localization with noisy distance measurements IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING Biswas, P., Liang, T., Toh, K., Ye, Y., Wang, T. 2006; 3 (4): 360-371

  View details for DOI 10.1109/TASE.2006.877401

  View details for Web of Science ID 000241124200003

• Improved complexity results on solving real-number linear feasibility problems MATHEMATICAL PROGRAMMING Ye, Y. Y. 2006; 106 (2): 339-363

  View details for DOI 10.1007/s10107-005-0610-7

  View details for Web of Science ID 000235062200007

• Lot-sizing scheduling with batch setup times JOURNAL OF SCHEDULING Chen, B., Ye, Y. Y., Zhang, J. W. 2006; 9 (3): 299-310

  View details for DOI 10.1007/s10951-006-8265-7

  View details for Web of Science ID 000237397600006

• Semidefinite Programming Based Algorithms for Sensor Network Localization ACM TRANSACTIONS ON SENSOR NETWORKS Biswas, P., Lian, T., Wang, T., Ye, Y. 2006; 2 (2)

  View details for Web of Science ID 000205012900003

• 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 So, A. M., Zhang, J., Ye, Y. SPRINGER-VERLAG BERLIN. 2006: 224–235

  View details for Web of Science ID 000240348600020

• A Semidefinite Programming Approach to Tensegrity Theory and Realizability of Graphs 17th ACM-SIAM Symposium on Discrete Algorithms So, A. M., Ye, Y. SIAM. 2006: 766–775

  View details for Web of Science ID 000281596300084

• Area Editors' Statements OPERATIONS RESEARCH Fourer, R., Hazen, G. B., Oren, S. S., Broadie, M. N., Duenyas, I., Song, J. S., Simester, D., Kress, M., Ye, Y. Y., Trick, M. A., Graves, S. C., Zenios, S. A., van Ryzin, G. J., Henderson, S. G., Kumar, S., Balakrishnan, A., Ball, M. O. 2006; 54 (1): 5-10

  View details for DOI 10.1287/opre.1050.0269

  View details for Web of Science ID 000235596200002

• SpaseLoc: An adaptive subproblem algorithm for scalable wireless sensor network localization SIAM JOURNAL ON OPTIMIZATION Carter, M. W., Jin, H. H., Saunders, M. A., Ye, Y. 2006; 17 (4): 1102-1128

  View details for DOI 10.1137/040621600

  View details for Web of Science ID 000244631800007

• Approximation algorithms for metric facility location problems SIAM JOURNAL ON COMPUTING Mahdian, M., Ye, Y., Zhang, J. 2006; 36 (2): 411-432

  View details for DOI 10.1137/S0097539703435716

  View details for Web of Science ID 000240043700006

• Distributed method for solving semidefinite programs arising from ad hoc wireless sensor network localization Conference on Multiscale Optimization Methods and Applications Biswas, P., Ye, Y. Y. SPRINGER. 2006: 69–84

  View details for Web of Science ID 000234830500002

• Leontief Economies Encode Nonzero Sum Two-Player Games 17th ACM-SIAM Symposium on Discrete Algorithms Codenotti, B., Saberi, A., Varadarajan, K., Ye, Y. SIAM. 2006: 659–667

  View details for Web of Science ID 000281596300072

• A new complexity result on solving the Markov decision problem MATHEMATICS OF OPERATIONS RESEARCH Ye, Y. Y. 2005; 30 (3): 733-749

  View details for DOI 10.1287/moor.1050.0149

  View details for Web of Science ID 000231792300011

• A multiexchange local search algorithm for the capacitated facility location problem MATHEMATICS OF OPERATIONS RESEARCH Zhang, J. W., Chen, B., Ye, Y. Y. 2005; 30 (2): 389-403

  View details for DOI 10.1287/moor.1040.0125

  View details for Web of Science ID 000230035200007

• On solving univariate sparse polynomials in logarithmic time Conference on Foundations of Computational Mathematics (FoCM) Rojas, J. M., Ye, Y. Y. 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

• On solving coverage problems in a wireless sensor network using Voronoi diagrams 1st International Workshop on Internet and Network Economics So, A. M., Ye, Y. Y. SPRINGER-VERLAG BERLIN. 2005: 584–593

  View details for Web of Science ID 000234851600058

• Computing the Arrow-Debreu competitive market equilibrium and its extensions 1st International Conference on Algorithmic Applications in Management Ye, Y. Y. SPRINGER-VERLAG BERLIN. 2005: 3–5

  View details for Web of Science ID 000230475100002

• Semidefinite programming algorithms for sensor network localization using angle information 39th Asilomar Conference on Signals, Systems and Computers Biswas, P., Aghajan, H., Ye, Y. IEEE. 2005: 220–224

  View details for Web of Science ID 000238142000040

• On approximating complex quadratic optimization problems via semidefinite programming relaxations 11th International Integer Programming and Combinatorial Optimization Conference So, A. M., Zhang, J. W., Ye, Y. Y. SPRINGER-VERLAG BERLIN. 2005: 125–135

  View details for Web of Science ID 000230361400010

• Theory of Semidefinite Programming for Sensor Network Localization 16th Annual ACM-SIAM Symposium on Discrete Algorithms So, A. M., Ye, Y. SIAM. 2005: 405–414

  View details for Web of Science ID 000281595800046

• Exchange market equilibria with Leontief's utility: Freedom of pricing leads to rationality 1st International Workshop on Internet and Network Economics Ye, Y. Y. SPRINGER-VERLAG BERLIN. 2005: 14–23

  View details for Web of Science ID 000234851600003

• Improved approximations for max set splitting and max NAE SAT DISCRETE APPLIED MATHEMATICS Zhang, J. W., Ye, Y. Y., Han, Q. M. 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

• A multi-exchange local search algorithm for the capacitated facility location problem - (Extended abstract) 10th International Integer Programming and Combinatorial Optimization Conference Zhang, J. W., Chen, B., Ye, Y. Y. SPRINGER-VERLAG BERLIN. 2004: 219–233

  View details for Web of Science ID 000222230000017

• Improved combinatorial approximation algorithms for the k-level facility location problem SIAM JOURNAL ON DISCRETE MATHEMATICS Ageev, A., Ye, Y. Y., Zhang, J. W. 2004; 18 (1): 207-217

  View details for DOI 10.1137/S0895480102417215

  View details for Web of Science ID 000224348700015

• Semidefinite programming for ad hoc wireless sensor network localization 3rd International Symposium on Information Processing in Sensor Networks Biswas, P., Ye, Y. Y. ASSOC COMPUTING MACHINERY. 2004: 46–54

  View details for Web of Science ID 000222055900006

• Approximating the 2-catalog segmentation problem using semidefinite programming relaxations 1st International Conference on Optimization Methods and Software (OMS2002) Xu, D. C., Ye, Y. Y., Zhang, J. W. TAYLOR & FRANCIS LTD. 2003: 705–19

  View details for DOI 10.1080/10556780310001634082

  View details for Web of Science ID 000187296300007

• An approximation algorithm for scheduling two parallel machines with capacity constraints DISCRETE APPLIED MATHEMATICS Yang, H., Ye, Y. Y., Zhang, J. W. 2003; 130 (3): 449-467

  View details for DOI 10.1016/S0166-218X(02)00601-7

  View details for Web of Science ID 000185241300006

• 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 Ye, Y. Y., Zhang, J. W. SPRINGER-VERLAG BERLIN. 2003: 178–187

  View details for Web of Science ID 000185994700016

• Improved combinatorial approximation algorithms for the k-level facility location problem 30th International Colloquium on Automata, Languages and Programming (ICALP 2003) Ageev, A., Ye, Y. Y., Zhang, J. W. SPRINGER-VERLAG BERLIN. 2003: 145–156

  View details for Web of Science ID 000185145700013

• New results on quadratic minimization SIAM JOURNAL ON OPTIMIZATION Ye, Y. Y., Zhang, S. Z. 2003; 14 (1): 245-267

  View details for DOI 10.1137/S105262340139001X

  View details for Web of Science ID 000185130700010

• 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 Mahdian, M., Ye, Y. Y., Zhang, J. W. SPRINGER-VERLAG BERLIN. 2003: 129–140

  View details for Web of Science ID 000185994700012

• A note on the maximization version of the multi-level facility location problem OPERATIONS RESEARCH LETTERS Zhang, J. W., Ye, Y. Y. 2002; 30 (5): 333-335

  View details for Web of Science ID 000178894600007

• An improved rounding method and semidefinite programming relaxation for graph partition 17th International Symposium of the Mathematical-Programming-Society Han, Q. M., Ye, Y. Y., Zhang, J. W. SPRINGER. 2002: 509–35

  View details for DOI 10.1007/s101070100288

  View details for Web of Science ID 000176303700007

• Improved approximation algorithms for metric facility location problems 5th International Workshop on Approximation Algorithms for Combinatorial Optimization Mahdian, M., Ye, Y. Y., Zhang, J. W. SPRINGER-VERLAG BERLIN. 2002: 229–242

  View details for Web of Science ID 000187294200020

• Approximating maximum stable set and minimum graph coloring problems with the positive semidefinite relaxation International Conference on Complementarity 99 (ICCP99) Benson, S. J., Ye, Y. SPRINGER. 2001: 1–17

  View details for Web of Science ID 000168052500001

• Blind Channel Equalization and Approximation Algorithms IEEE Trans. on Signal Processing Li, B. 2001; 49 (11): 2823-2831
• A .699-approximation algorithm for Max-Bisection Mathematical Programming Ye, Y. 2001; 90: 101-111
• On smoothing methods for the P0 matrix linear complementarity problem SIAM J. Optimization Chen, X., Ye, Y. 2001; 11: 341-363
• An efficient algorithm for minimizing a sum of P-norms SIAM J. Optimization Xue, G., Ye, Y. 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 Vavasis, S., Ye, Y. edited by Zhang, et al, S. 2000: 233–243
• Application of Semidefinite Programming to Circuit Partitioning Approximation and Complexity in Numerical Optimization Choi, C., Ye, Y. 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 Bai, E., Fu, M., Tempo, R., Ye, Y. 2000
• Solving large-scale sparse semidefinite programs for combinatorial optimization SIAM J. Optimization Benson, S., Ye, Y., Zhang, X. 2000; 10: 443-461
• Probabilistic Analysis of an Infeasible Primal--Dual Algorithm for Linear Programming Mathematics of Operations Research Anstreicher, K., Ji, J., Potra, F., Ye, Y. 1999; 24: 176-192
• On a homogeneous algorithm for the monotone complementarity problem Mathematical Programming Andersen, E., Ye, Y. 1999; 84: 375-400
• Bounded Error Parameter Estimation: A Sequential Analytic Center Approach IEEE Transactions on Automatic Control Bai, E., Ye, Y., Tempo, R. 1999; 6 (44): 1107-1117
• On Homotopy-Smoothing Methods for Variational Inequalities SIAM J. Control & Optimization Chen, X., Ye, Y. 1999; 37: 589-616
• Infeasible-start primal-dual methods and infeasibility detectors for nonlinear programming problems Mathematical Programming Nesterov, Yu., Todd, M., J., Ye, Y. 1999; 84: 227-267
• Constrained Logarithmic Least Squares in Parameter Estimation IEEE Transactions on Automatic Control Bai, E., Ye, Y. 1999; 1 (44): 182-185
• A computational study of the homogeneous algorithm for large-scale convex optimization Computational Optimization and Applications Andersen, E., Ye, Y. 1998; 10: 243-269
• Semidefinite Relaxations, Multivariate Normal Distributions, and Order Statistics Handbook of Combinatorial Optimization Bertsimas, D., Ye, Y. 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 Ye, Y. 1998; 80: 195-212
• Approximation algorithms for quadratic programming Journal of Combinatorial Optimization Fu, M., Luo, Z., Q., Ye, Y. 1998; 1 (2): 29-50
• Approximate Farkas lemmas and stopping rules for iterative infeasible-point algorithms for linear programming Mathematical Programming Todd, M., J., Ye, Y. 1998; 81: 1-22
• An infeasible interior-point algorithm for solving primal and dual geometric programs Mathematical Programming Kortanek, K., O., Xu, X., Ye, Y. 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 Andersen, E., Ye, Y. 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 Jansen, B., Roos, C., Terlaky, T., Ye, Y. 1997; 76: 117-130
• Complexity analysis of the analytic center cutting plane method that uses multiple cuts Mathematical Programming Ye, Y. 1997; 78: 85-104
• On homogeneous and self-dual algorithm for LCP Mathematical Programming Ye, Y. 1997; 76: 211-222
• Efficient algorithms for minimizing a sum of Euclidean norms with applications SIAM J. Optimization Xue, G., Ye, Y. 1997; 7: 1017-1036
• A primal-dual interior-point method whose running time depends only on the constraint matrix Mathematical Programming Vavasis, S., Ye, Y. 1996; 74: 79-120
• How partial knowledge helps to solve linear programs Journal of Complexity Ye, Y. 1996; 12: 480-491
• Complexity analysis of an interior-point cutting plane method for convex feasibility problem SIAM J. Optimization Goffin, J., Luo, Z., Ye, Y. 1996; 6: 638-652
• Combining interior-point and pivoting algorithms for linear programming Management Science Andersen, E., D., Ye, Y. 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 Todd, M., Ye, Y. 1996; 62: 233-252
• A asymptotical O(√nL) -iteration path-following linear programming algorithm that uses long steps SIAM J. Optimization Ye, Y. 1996; 6: 570-586
• Interior-point methods for nonlinear complementarity problem Journal of Optimization Theory and Application Potra, F., Ye, Y. 1996; 68
• Identifying an optimal basis in linear programming Annals of Operations Research Vavasis, S., Ye, Y. 1996; 62: 565-572
• A simplified homogeneous and self-dual linear programming algorithm and its implementation Annals of Operations Research Xu, X., Hung, P., Ye, Y. 1996; 62: 151-172
• A surface of analytic centers and infeasible-interior-point algorithms for linear programming Mathematics of Operations Research Mizuno, S., Todd, M., Ye, Y. 1995; 20: 135-162
• On the von Neumann economic growth problem Mathematics Operations Research Ye, Y. 1995; 20: 617-633
• Condition numbers for polyhedra with real number data Operations Research Letters Vavasis, S., Ye, Y. 1995; 17: 209-214
• A generalized homogeneous and self-dual linear programming algorithm Operations Research Letters Xu, X., Ye, Y. 1995; 17
• On the convergence of the iteration sequence in primal-dual interior-point methods Mathematical Programming Tapia, R., Zhang, Y., Ye, Y. 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 Spector, Y., Tishler, A., Ye, Y. 1995; 41: 1679-1692
• A convergent algorithm for quantile regression with smoothing splines Computational Statistics & Data Analysis Bosch, R., J., Ye, Y., Woodworth, G., G. 1995; 19: 613-630
• Specially structured uncapacitated facility location problems Operations Research Jones, P., Lowe, T., Muller, G., Xu, N., Ye, Y., Zydiak, J. 1995; 43: 661-669
• Combining binary search and Newton's method to compute real roots for a class of real functions Journal of Complexity Ye, Y. 1994; 10: 271-280
• ON THE COMPLEXITY OF A COLUMN GENERATION ALGORITHM FOR CONVEX OR QUASI-CONVEX FEASIBILITY PROBLEMS Conference on Large Scale Optimization Goffin, J. L., Luo, Z. Q., Ye, Y. Y. 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 Ye, Y. 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 Goffin, J., Luo, Z., Ye, Y. 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 Ji, J., Ye, Y. 1994; 4: 512-520
• Toward probabilistic analysis of interior-point algorithms for linear programming Mathematics of Operations Research Ye, Y. 1994; 19: 38-52
• An $O(\sqrt{n}L)$-iteration homogeneous and self-dual linear programming algorithm Mathematics of Operations Research Ye, Y., Todd, M., Mizuno, S. 1994; 19: 53-67
• An accelerated interior-point method whose running time depends only on $A$ Vavasis, S., Ye, Y. 1994
• A decomposition variant of the potential reduction algorithm for linear programming Management Science Kaliski, J., Ye, Y. 1993; 39: 757-776
• Average performance of a self-dual interior-point algorithm for linear programming Complexity in Numerical Optimization Anstreicher, K., Ji, J., Potra, F., Ye, Y. edited by Pardalos, P. World Scientific, New Jersey. 1993: 1–15
• Translation cuts for convex minimization Complexity in Numerical Optimization Burke, J., Goldstein, A., Tseng, P., Ye, Y. 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. Pardalos, P., Ye, Y., Han, C., Kaliski, J. 1993; 14: 1048-1060
• Near-boundary behavior of the primal-dual potential reduction algorithm for linear programming Mathematical Programming Ye, Y., Kortanek, K., Kaliski, J., Huang, S. 1993; 58: 243-255
• Minimal adjustment costs, factor demands, and seasonal time-of-use electricity rates Resource and Energy Economics Tishler, A., Ye, Y. 1993; 15: 313-335
• An extension of the potential reduction algorithm for solving LCP with priority goals Linear Algebra and its Applications Kaliski, J., Ye, Y. 1993; 193: 35-50
• A quadratically convergent polynomial interior-point algorithm for solving entropy optimization problems SIAM J. on Optimization Potra, F., Ye, Y. 1993; 3: 843-860
• On quadratic and $O(\sqrt{n}L)$ convergence of a predictor- corrector algorithm for LCP Mathematical Programming Ye, Y., Anstreicher, K. 1993; 62: 537-552
• On finding an interior point on the optimal face of linear programs Mathematical Programming Mehrotra, S., Ye, Y. 1993; 62: 497-516
• On adaptive-step primal-dual interior-point algorithms for linear programming Mathematics of Operations Research Mizuno, S., Todd, M., Ye, Y. 1993; 18: 964-981
• A quadratically convergent $O(\sqrt{n}L)$-iteration algorithm for linear programming Mathematical Programming Ye, Y., G\"uler, O., Tapia, R., Zhang, Y. 1993; 59: 151-162
• A fully polynomial-time approximation algorithm for computing a stationary point of the general LCP Mathematics of Operations Research Ye, Y. 1993; 18: 334-345
• Convergence behavior of some interior-point algorithms Mathematical Programming G\"uler, O., Ye, Y. 1993; 60: 215-228
• Extensions of the potential reduction algorithm for linear programming Journal of Optimization Theory and Applications Ye, Y. 1992; 193: 35-50
• On the Q-order of convergence of interior-point algorithms for linear programming Ye, Y. 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, Ye, Y. 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 Ye, Y. edited by Floudas, C., Pardalos, P. Princeton University Press, NJ. 1992: 1
• On affine scaling algorithms for nonconvex quadratic programming Mathematical Programming Ye, Y. 1992; 56: 285-300
• Comparative analysis of affine scaling algorithms for linear programming Mathematical Programming Ye, Y. 1992; 52: 405-414
• A potential reduction algorithm allowing column generation SIAM J. on Optimization Ye, Y. 1992; 2: 7-20
• On the finite convergence of interior-point algorithms for linear programming Mathematical Programming Ye, Y. 1992; 57: 325-335
• Implementation of interior-point algorithms for some entropy optimization problems Optimization Methods and Software Han, C., Pardalos, P., Ye, Y. 1992; 1: 71-80
• An interior point potential reduction algorithm for the linear complementarity problem Mathematical Programming Kojima, M., Megiddo, N., Ye, Y. 1992; 54: 267-279
• A class of LCPs solvable in polynomial time Linear Algebra and its Applications Ye, Y., Pardalos, P. 1991; 152: 3-17
• Interior-point algorithms for quadratic programming Recent Developments in Mathematical Programming Ye, Y. 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 Kortanek, K., Potra, F., Ye, Y. 1991; 152: 169-189
• Interior-point algorithms for solving nonlinear optimization problems COAL Newsletter Han, C., Pardalos, P., Ye, Y. 1991; 19: 45-54
• Convergence behavior of Karmarkar's projective algorithm for solving a simple linear program Operations Research Letters Kaliski, J., Ye, Y. 1991; 10: 389-393
• An $O(n^3L)$ potential reduction algorithm for linear programming Mathematical Programming Ye, Y. 1991; 50: 239-258
• Algorithms for the solution of quadratic knapsack problems Linear Algebra and its Applications Pardalos, P., Han, C., Ye, Y. 1991; 152: 69-91
• Computational aspects of an interior point algorithm for quadratic programming problems with box constraints Large-Scale Numerical Optimization Han, C., Pardalos, P., Ye, Y. edited by Coleman, T., F., Li, Y. SIAM, Philadelphia. 1990: 1
• Interior-point algorithms for global optimization Annals of Operations Research Ye, Y. 1990; 25: 59-74
• Containing and shrinking ellipsoids in the path-following algorithm Mathematical Programming Ye, Y., Todd, M. 1990; 47: 1-9
• A centered projective algorithm for linear programming Mathematics of Operations Research Todd, M., Ye, Y. 1990; 15: 508-529
• A ``build-down'' scheme for linear programming Mathematical Programming Ye, Y. 1990; 46: 61-72
• Recovering optimal basic variables in Karmarkar's polynomial algorithm for linear programming Mathematics of Operations Research Ye, Y. 1990; 15: 564-571
• A class of projective transformations for linear programming SIAM J. on Computing Ye, Y. 1990; 19: 457-466
• AN EXTENSION OF KARMARKAR PROJECTIVE ALGORITHM FOR CONVEX QUADRATIC-PROGRAMMING MATHEMATICAL PROGRAMMING Ye, Y. Y., Tse, E. 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 Ye, Y., Tse, E. 1989; 44: 157-179
• Eliminating columns in the simplex method for linear programming Journal of Optimization Theory and Applications Ye, Y. 1989; 63: 103-111
• RECOVERING OPTIMAL DUAL SOLUTIONS IN KARMARKARS POLYNOMIAL ALGORITHM FOR LINEAR-PROGRAMMING MATHEMATICAL PROGRAMMING Ye, Y. Y., Kojima, M. 1987; 39 (3): 305-317

  View details for Web of Science ID A1987L163200006

• KARMARKAR ALGORITHM AND THE ELLIPSOID METHOD OPERATIONS RESEARCH LETTERS Ye, Y. Y. 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 Ye, Y., Kojima, M. 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 Ye, Y. 1983; 2
• Directed graphs, linear Diophantine equations, and ergodic problems of stochastic matrices, English Edit. Journal of Huazhong University of Science and Technology Ye, Y. 1982; 2