| Year |
Citation |
Score |
| 2020 |
Gao W, Goldfarb D, Curtis FE. ADMM for multiaffine constrained optimization Optimization Methods & Software. 35: 257-303. DOI: 10.1080/10556788.2019.1683553 |
0.464 |
|
| 2019 |
Gao W, Goldfarb D. Quasi-Newton methods: superlinear convergence without line searches for self-concordant functions Optimization Methods & Software. 34: 194-217. DOI: 10.1080/10556788.2018.1510927 |
0.457 |
|
| 2018 |
Gao W, Goldfarb D. Block BFGS Methods Siam Journal On Optimization. 28: 1205-1231. DOI: 10.1137/16M1092106 |
0.37 |
|
| 2017 |
Mu C, Hsu DJ, Goldfarb D. Greedy Approaches to Symmetric Orthogonal Tensor Decomposition Siam Journal On Matrix Analysis and Applications. 38: 1210-1226. DOI: 10.1137/16M1087734 |
0.338 |
|
| 2017 |
Wang X, Ma S, Goldfarb D, Liu W. Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization Siam Journal On Optimization. 27: 927-956. DOI: 10.1137/15M1053141 |
0.582 |
|
| 2017 |
Goldfarb D, Mu C, Wright J, Zhou C. Using negative curvature in solving nonlinear programs Computational Optimization and Applications. 68: 479-502. DOI: 10.1007/S10589-017-9925-6 |
0.452 |
|
| 2016 |
Mu C, Zhang Y, Wright J, Goldfarb D. Scalable Robust Matrix Recovery: Frank--Wolfe Meets Proximal Methods Siam Journal On Scientific Computing. 38. DOI: 10.1137/15M101628X |
0.533 |
|
| 2015 |
Mu C, Hsu D, Goldfarb D. Successive rank-one approximations for nearly orthogonally decomposable symmetric tensors Siam Journal On Matrix Analysis and Applications. 36: 1638-1659. DOI: 10.1137/15M1010890 |
0.399 |
|
| 2015 |
Qin ZT, Goldfarb D, Ma S. An alternating direction method for total variation denoising Optimization Methods & Software. 30: 594-615. DOI: 10.1080/10556788.2014.955100 |
0.774 |
|
| 2014 |
Goldfarb D, Qin Z(. Robust Low-Rank Tensor Recovery: Models and Algorithms Siam Journal On Matrix Analysis and Applications. 35: 225-253. DOI: 10.1137/130905010 |
0.553 |
|
| 2014 |
Aybat NS, Goldfarb D, Ma S. Efficient algorithms for robust and stable principal component pursuit problems Computational Optimization and Applications. 58: 1-29. DOI: 10.1007/S10589-013-9613-0 |
0.663 |
|
| 2014 |
Scheinberg K, Goldfarb D, Bai X. Fast First-Order Methods for Composite Convex Optimization with Backtracking Foundations of Computational Mathematics. 14: 389-417. DOI: 10.1007/S10208-014-9189-9 |
0.487 |
|
| 2013 |
Qin Z, Scheinberg K, Goldfarb D. Efficient block-coordinate descent algorithms for the Group Lasso Mathematical Programming Computation. 5: 143-169. DOI: 10.1007/S12532-013-0051-X |
0.725 |
|
| 2013 |
Huang B, Ma S, Goldfarb D. Accelerated Linearized Bregman Method Journal of Scientific Computing. 54: 428-453. DOI: 10.1007/S10915-012-9592-9 |
0.714 |
|
| 2013 |
Goldfarb D, Ma S, Scheinberg K. Fast alternating linearization methods for minimizing the sum of two convex functions Mathematical Programming. 141: 349-382. DOI: 10.1007/S10107-012-0530-2 |
0.688 |
|
| 2012 |
Goldfarb D, Ma S. Fast Multiple-Splitting Algorithms for Convex Optimization Siam Journal On Optimization. 22: 533-556. DOI: 10.1137/090780705 |
0.674 |
|
| 2012 |
Wen Z, Yin W, Zhang H, Goldfarb D. On the convergence of an active-set method for ℓ1 minimization Optimization Methods & Software. 27: 1127-1146. DOI: 10.1080/10556788.2011.591398 |
0.75 |
|
| 2011 |
Goldfarb D, Ma S. Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization Foundations of Computational Mathematics. 11: 183-210. DOI: 10.1007/S10208-011-9084-6 |
0.694 |
|
| 2011 |
Ma S, Goldfarb D, Chen L. Fixed point and Bregman iterative methods for matrix rank minimization Mathematical Programming. 128: 321-353. DOI: 10.1007/S10107-009-0306-5 |
0.752 |
|
| 2011 |
Chen L, Goldfarb D. An interior-point piecewise linear penalty method for nonlinear programming Mathematical Programming. 128: 73-122. DOI: 10.1007/S10107-009-0296-3 |
0.604 |
|
| 2010 |
Wen Z, Yin W, Goldfarb D, Zhang Y. A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation Siam Journal On Scientific Computing. 32: 1832-1857. DOI: 10.1137/090747695 |
0.732 |
|
| 2010 |
Wen Z, Goldfarb D, Yin W. Alternating direction augmented Lagrangian methods for semidefinite programming Mathematical Programming Computation. 2: 203-230. DOI: 10.1007/S12532-010-0017-1 |
0.765 |
|
| 2009 |
Goldfarb D, Wen Z, Yin W. A Curvilinear Search Method for $p$-Harmonic Flows on Spheres Siam Journal On Imaging Sciences. 2: 84-109. DOI: 10.1137/080726926 |
0.699 |
|
| 2009 |
Wen Z, Goldfarb D. A Line Search Multigrid Method for Large-Scale Nonlinear Optimization Siam Journal On Optimization. 20: 1478-1503. DOI: 10.1137/08071524X |
0.655 |
|
| 2009 |
Goldfarb D, Yin W. Parametric Maximum Flow Algorithms for Fast Total Variation Minimization Siam Journal On Scientific Computing. 31: 3712-3743. DOI: 10.1137/070706318 |
0.598 |
|
| 2008 |
Erdogan E, Goldfarb D, Iyengar G. Robust Active Portfolio Management Journal of Computational Finance. 11: 71-98. DOI: 10.21314/Jcf.2008.187 |
0.37 |
|
| 2008 |
Yin W, Osher S, Goldfarb D, Darbon J. Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing Siam Journal On Imaging Sciences. 1: 143-168. DOI: 10.1137/070703983 |
0.647 |
|
| 2007 |
Yin W, Goldfarb D, Osher S. The Total Variation Regularized $L^1$ Model for Multiscale Decomposition Multiscale Modeling & Simulation. 6: 190-211. DOI: 10.1137/060663027 |
0.548 |
|
| 2007 |
Yin W, Goldfarb D, Osher S. A comparison of three total variation based texture extraction models Journal of Visual Communication and Image Representation. 18: 240-252. DOI: 10.1016/J.Jvcir.2007.01.004 |
0.569 |
|
| 2006 |
Chen L, Goldfarb D. Interior-point ℓ 2 -penalty methods for nonlinear programming with strong global convergence properties Mathematical Programming. 108: 1-36. DOI: 10.1007/S10107-005-0701-5 |
0.615 |
|
| 2005 |
Goldfarb D, Yin W. Second-order Cone Programming Methods for Total Variation-Based Image Restoration Siam Journal On Scientific Computing. 27: 622-645. DOI: 10.1137/040608982 |
0.679 |
|
| 2005 |
Osher S, Burger M, Goldfarb D, Xu J, Yin W. An Iterative Regularization Method for Total Variation-Based Image Restoration Multiscale Modeling & Simulation. 4: 460-489. DOI: 10.1137/040605412 |
0.643 |
|
| 2005 |
Goldfarb D, Scheinberg K. Product-form Cholesky factorization in interior point methods for second-order cone programming Mathematical Programming. 103: 153-179. DOI: 10.1007/S10107-004-0556-1 |
0.474 |
|
| 2005 |
Yin W, Goldfarb D, Osher S. Image cartoon-texture decomposition and feature selection using the total variation regularized L 1 functional Lecture Notes in Computer Science. 73-84. DOI: 10.1007/11567646_7 |
0.551 |
|
| 2004 |
Goldfarb D, Scheinberg K. A product-form Cholesky factorization method for handling dense columns in interior point methods for linear programming Mathematical Programming. 99: 1-34. DOI: 10.1007/S10107-003-0377-7 |
0.426 |
|
| 2003 |
Goldfarb D, Iyengar G. Robust portfolio selection problems Mathematics of Operations Research. 28: 1-38. DOI: 10.1287/Moor.28.1.1.14260 |
0.389 |
|
| 2003 |
Goldfarb D, Iyengar G. Robust convex quadratically constrained programs Mathematical Programming. 97: 495-515. DOI: 10.1007/S10107-003-0425-3 |
0.412 |
|
| 2003 |
Alizadeh F, Goldfarb D. Second-order cone programming Mathematical Programming. 95: 3-51. DOI: 10.1007/S10107-002-0339-5 |
0.473 |
|
| 2002 |
Goldfarb D, Jin Z, Lin Y. A polynomial dual simplex algorithm for the generalized circulation problem Mathematical Programming. 91: 271-288. DOI: 10.1007/S101070100248 |
0.481 |
|
| 2002 |
Goldfarb D, Lin Y. Combinatorial interior point methods for generalized network flow problems Mathematical Programming. 93: 227-246. DOI: 10.1007/S10107-002-0333-Y |
0.52 |
|
| 1999 |
Goldfarb D, Gte ZJ. An O ( Nm )-Time Network Simplex Algorithm for the Shortest Path Problem Operations Research. 47: 445-448. DOI: 10.1287/Opre.47.3.445 |
0.412 |
|
| 1999 |
Goldfarb D, Polyak R, Scheinberg K, Yuzefovich I. A Modified Barrier-Augmented Lagrangian Method for Constrained Minimization Computational Optimization and Applications. 14: 55-74. DOI: 10.1023/A:1008705028512 |
0.477 |
|
| 1999 |
Goldfarb D, Scheinberg K. On parametric semidefinite programming Applied Numerical Mathematics. 29: 361-377. DOI: 10.1016/S0168-9274(98)00102-0 |
0.399 |
|
| 1999 |
Goldfarb D, Jin Z. A new scaling algorithm for the minimum cost network flow problem Operations Research Letters. 25: 205-211. DOI: 10.1016/S0167-6377(99)00047-4 |
0.433 |
|
| 1998 |
Goldfarb D, Scheinberg K. Interior Point Trajectories in Semidefinite Programming Siam Journal On Optimization. 8: 871-886. DOI: 10.1137/S105262349630009X |
0.462 |
|
| 1998 |
Armstrong RD, Chen W, Goldfarb D, Jin Z. Strongly polynomial dual simplex methods for the maximum flow problem Mathematical Programming. 80: 17-33. DOI: 10.1007/Bf01582129 |
0.436 |
|
| 1997 |
Goldfarb D, Jin Z, Orlin JB. Polynomial-time highest-gain augmenting path algorithms for the generalized circulation problem Mathematics of Operations Research. 22: 793-802. DOI: 10.1287/Moor.22.4.793 |
0.495 |
|
| 1997 |
Goldfarb D, Chen W. On strongly polynomial dual simplex algorithms for the maximum flow problem Mathematical Programming. 78: 159-168. DOI: 10.1007/Bf02614368 |
0.434 |
|
| 1996 |
Goldfarb D, Jin Z. A Faster Combinatorial Algorithm for the Generalized Circulation Problem Mathematics of Operations Research. 21: 529-539. DOI: 10.1287/Moor.21.3.529 |
0.499 |
|
| 1995 |
Goldfarb D, Shaw DX. On the complexity of a class of projective interior point methods Mathematics of Operations Research. 20: 116-134. DOI: 10.1287/Moor.20.1.116 |
0.476 |
|
| 1995 |
Eckstein J, Boduroğlu Iİ, Polymenakos LC, Goldfarb D. Data-Parallel Implementations of Dense Simplex Methods on the Connection Machine CM-2 Informs Journal On Computing. 7: 402-416. DOI: 10.1287/Ijoc.7.4.402 |
0.383 |
|
| 1994 |
Shaw DX, Goldfarb D. A Path-Following Projective Interior Point Method For Linear Programming* Siam Journal On Optimization. 4: 65-85. DOI: 10.1137/0804003 |
0.486 |
|
| 1994 |
Choi IC, Goldfarb D. On solution-containing ellipsoids in linear programming Journal of Optimization Theory and Applications. 80: 161-173. DOI: 10.1007/Bf02196599 |
0.426 |
|
| 1993 |
Goldfarb D, Wang S. Partial-Update Newton Methods for Unary, Factorable, and Partially Separable Optimization Siam Journal On Optimization. 3: 382-397. DOI: 10.1137/0803017 |
0.5 |
|
| 1993 |
Goldfarb D, Hao J. On the maximum capacity augmentation algorithm for the maximum flow problem Discrete Applied Mathematics. 47: 9-16. DOI: 10.1016/0166-218X(93)90148-H |
0.467 |
|
| 1993 |
Goldfarb D, Liu S. An O( n 3 L )primal-dual potential reduction algorithm for solving convex quadratic programs Mathematical Programming. 61: 161-170. DOI: 10.1007/Bf01582145 |
0.502 |
|
| 1993 |
Choi IC, Goldfarb D. Exploiting special structure in a primal-dual path-following algorithm Mathematical Programming. 58: 33-52. DOI: 10.1007/Bf01581258 |
0.513 |
|
| 1992 |
Goldfarb D, Hao J. Polynomial-time primal simplex algorithms for the minimum cost network flow problem Algorithmica. 8: 145-160. DOI: 10.1007/Bf01758840 |
0.421 |
|
| 1992 |
Forrest JJ, Goldfarb D. Steepest-edge simplex algorithms for linear programming Mathematical Programming. 57: 341-374. DOI: 10.1007/Bf01581089 |
0.54 |
|
| 1991 |
Goldfarb D, Liu S, Wang S. A Logarithmic Barrier Function Algorithm for Quadratically Constrained Convex Quadratic Programming Siam Journal On Optimization. 1: 252-267. DOI: 10.1137/0801017 |
0.524 |
|
| 1991 |
Goldfarb D, Hao J. On strongly polynomial variants of the network simplex algorithm for the maximum flow problem Operations Research Letters. 10: 383-387. DOI: 10.1016/0167-6377(91)90039-R |
0.433 |
|
| 1991 |
Goldfarb D, Liu S. An OL ( n 3 ) primal interior point algorithm for convex quadratic programming Mathematical Programming. 49: 325-340. DOI: 10.1007/Bf01588795 |
0.484 |
|
| 1991 |
Goldfarb D, Xiao D. A primal projective interior point method for linear programming Mathematical Programming. 51: 17-43. DOI: 10.1007/Bf01586924 |
0.487 |
|
| 1991 |
Goldfarb D, Hao J, Kai S. Shortest path algorithms using dynamic breadth-first search Networks. 21: 29-50. DOI: 10.1002/Net.3230210105 |
0.365 |
|
| 1990 |
Goldfarb D, Hao J, Kai S. Efficient shortest path simplex algorithms Operations Research. 38: 624-628. DOI: 10.1287/Opre.38.4.624 |
0.382 |
|
| 1990 |
Goldfarb D, Hao J, Kai S. Anti-stalling Pivot rules for the network simplex algorithm Networks. 20: 79-91. DOI: 10.1002/Net.3230200108 |
0.415 |
|
| 1989 |
Goldfarb D, Mehrotra S. A Self-Correcting Version of Karmarkar’s Algorithm Siam Journal On Numerical Analysis. 26: 1006-1015. DOI: 10.1137/0726056 |
0.63 |
|
| 1988 |
Goldfarb D, Grigoriadis MD. A computational comparison of the dinic and network simplex methods for maximum flow Annals of Operations Research. 13: 81-123. DOI: 10.1007/Bf02288321 |
0.444 |
|
| 1988 |
Goldfarb D, Mehrotra S. A relaxed version of Karmarkar's method Mathematical Programming. 40: 289-315. DOI: 10.1007/Bf01580737 |
0.577 |
|
| 1988 |
Goldfarb D, Mehrotra S. Relaxed variants of Karmarkar's algorithm for linear programs with unknown optimal objective value Mathematical Programming. 40: 183-195. DOI: 10.1007/Bf01580729 |
0.66 |
|
| 1986 |
Goldfarb D. Efficient dual simplex algorithms for the assignment problem Mathematical Programming. 34: 372-372. DOI: 10.1007/Bf01582238 |
0.487 |
|
| 1983 |
Goldfarb D, Idnani A. A numerically stable dual method for solving strictly convex quadratic programs Mathematical Programming. 27: 1-33. DOI: 10.1007/Bf02591962 |
0.546 |
|
| 1982 |
Goldfarb D, Todd MJ. Modifications and implementation of the ellipsoid algorithm for linear programming Mathematical Programming. 23: 1-19. DOI: 10.1007/Bf01583776 |
0.505 |
|
| 1981 |
Bland RG, Goldfarb D, Todd MJ. Feature Article—The Ellipsoid Method: A Survey Operations Research. 29: 1039-1091. DOI: 10.1287/Opre.29.6.1039 |
0.415 |
|
| 1980 |
Goldfarb D. Curvilinear path steplength algorithms for minimization which use directions of negative curvature Mathematical Programming. 18: 31-40. DOI: 10.1007/Bf01588294 |
0.429 |
|
| 1979 |
Goldfarb D, Sit WY. Worst case behavior of the steepest edge simplex method Discrete Applied Mathematics. 1: 277-285. DOI: 10.1016/0166-218X(79)90004-0 |
0.367 |
|
| 1977 |
Goldfarb D, Reid JK. A practicable steepest-edge simplex algorithm Mathematical Programming. 12: 361-371. DOI: 10.1007/Bf01593804 |
0.495 |
|
| 1977 |
Goldfarb D. Matrix factorizations in optimization of nonlinear functions subject to linear constraints — an addendum Mathematical Programming. 12: 279-280. DOI: 10.1007/Bf01593793 |
0.319 |
|
| 1977 |
Goldfarb D. On the Bartels--Golub decomposition for linear programming bases Mathematical Programming. 13: 272-279. DOI: 10.1007/Bf01584343 |
0.496 |
|
| 1977 |
Goldfarb D. Generating conjugate directions without line searches using factorized variable metric updating formulas Mathematical Programming. 13: 94-110. DOI: 10.1007/Bf01584327 |
0.38 |
|
| 1976 |
Goldfarb D. Factorized variable metric methods for unconstrained optimization Mathematics of Computation. 30: 796-811. DOI: 10.1090/S0025-5718-1976-0423804-2 |
0.468 |
|
| 1976 |
Goldfarb D. Matrix factorizations in optimization of nonlinear functions subject to linear constraints Mathematical Programming. 10: 1-31. DOI: 10.1007/Bf01580651 |
0.465 |
|
| 1972 |
Goldfarb D. Modification Methods for Inverting Matrices and Solving Systems of Linear Algebraic Equations Mathematics of Computation. 26: 829-852. DOI: 10.1090/S0025-5718-1972-0317527-4 |
0.457 |
|
| 1970 |
Goldfarb D. A family of variable-metric methods derived by variational means Mathematics of Computation. 24: 23-26. DOI: 10.1090/S0025-5718-1970-0258249-6 |
0.41 |
|
| 1969 |
Goldfarb D. Extension of Davidon’s Variable Metric Method to Maximization Under Linear Inequality and Equality Constraints Siam Journal On Applied Mathematics. 17: 739-764. DOI: 10.1137/0117067 |
0.386 |
|
| 1968 |
Goldfarb D, Lapidus L. Conjugate Gradient Method for Nonlinear Programming Problems with Linear Constraints Industrial & Engineering Chemistry Fundamentals. 7: 142-151. DOI: 10.1021/I160025A024 |
0.427 |
|
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