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2020 – today
- 2024
[j43]Patrick R. Johnstone, Jonathan Eckstein
, Thomas Flynn, Shinjae Yoo:
Stochastic projective splitting. Comput. Optim. Appl. 87(2): 397-437 (2024)- [j42]Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo:
Correction to: Stochastic projective splitting. Comput. Optim. Appl. 87(2): 439 (2024) - 2022
- [j41]Patrick R. Johnstone, Jonathan Eckstein:
Projective splitting with forward steps. Math. Program. 191(2): 631-670 (2022) - 2021
- [j40]Patrick R. Johnstone, Jonathan Eckstein:
Single-forward-step projective splitting: exploiting cocoercivity. Comput. Optim. Appl. 78(1): 125-166 (2021) - [i7]Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn, Shinjae Yoo:
Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers. CoRR abs/2106.13067 (2021) - 2020
- [j39]Maicon Marques Alves, Jonathan Eckstein, Marina Geremia, Jefferson G. Melo:
Relative-error inertial-relaxed inexact versions of Douglas-Rachford and ADMM splitting algorithms. Comput. Optim. Appl. 75(2): 389-422 (2020) - [j38]Patrick R. Johnstone, Jonathan Eckstein:
Projective splitting with forward steps only requires continuity. Optim. Lett. 14(1): 229-247 (2020) - [j37]Jonathan Eckstein:
Deriving solution value bounds from the ADMM. Optim. Lett. 14(6): 1289-1303 (2020)
2010 – 2019
- 2019
- [j36]Jonathan Eckstein, Ai Kagawa, Noam Goldberg:
REPR: Rule-Enhanced Penalized Regression. INFORMS J. Optim. 1(2): 143-163 (2019) - [j35]Patrick R. Johnstone, Jonathan Eckstein:
Convergence Rates for Projective Splitting. SIAM J. Optim. 29(3): 1931-1957 (2019) - [i6]Patrick R. Johnstone, Jonathan Eckstein:
Single-Forward-Step Projective Splitting: Exploiting Cocoercivity. CoRR abs/1902.09025 (2019) - 2018
- [j34]Jonathan Eckstein:
Comments on a Simplified Form of Block-Iterative Operator Splitting, and an Asynchronous Algorithm Resembling the Multi-block Alternating Direction Method of Multipliers. J. Optim. Theory Appl. 176(3): 783-785 (2018) - [j33]Patrick L. Combettes, Jonathan Eckstein:
Asynchronous block-iterative primal-dual decomposition methods for monotone inclusions. Math. Program. 168(1-2): 645-672 (2018) - [j32]Jonathan Eckstein, Wang Yao:
Relative-error approximate versions of Douglas-Rachford splitting and special cases of the ADMM. Math. Program. 170(2): 417-444 (2018) - [i5]Patrick R. Johnstone, Jonathan Eckstein:
Projective Splitting with Forward Steps: Asynchronous and Block-Iterative Operator Splitting. CoRR abs/1803.07043 (2018) - [i4]Patrick R. Johnstone, Jonathan Eckstein:
Convergence Rates for Projective Splitting. CoRR abs/1806.03920 (2018) - [i3]Patrick R. Johnstone, Jonathan Eckstein:
Projective Splitting with Forward Steps only Requires Continuity. CoRR abs/1809.07180 (2018) - [i2]Jonathan Eckstein, Gyorgy Matyasfalvi:
Efficient Distributed-Memory Parallel Matrix-Vector Multiplication with Wide or Tall Unstructured Sparse Matrices. CoRR abs/1812.00904 (2018) - 2017
- [j31]Jonathan Eckstein, Wang Yao:
Approximate ADMM algorithms derived from Lagrangian splitting. Comput. Optim. Appl. 68(2): 363-405 (2017) - [j30]Jonathan Eckstein:
A Simplified Form of Block-Iterative Operator Splitting and an Asynchronous Algorithm Resembling the Multi-Block Alternating Direction Method of Multipliers. J. Optim. Theory Appl. 173(1): 155-182 (2017) - [c3]Jonathan Eckstein, Noam Goldberg, Ai Kagawa:
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement. ICML 2017: 1059-1067 - 2016
- [j29]Jonathan Eckstein, Deniz Eskandani, Jingnan Fan:
Multilevel Optimization Modeling for Risk-Averse Stochastic Programming. INFORMS J. Comput. 28(1): 112-128 (2016) - 2015
- [j28]Jonathan Eckstein, William E. Hart, Cynthia A. Phillips:
PEBBL: an object-oriented framework for scalable parallel branch and bound. Math. Program. Comput. 7(4): 429-469 (2015) - 2013
- [j27]Jonathan Eckstein, Paulo J. S. Silva:
A practical relative error criterion for augmented Lagrangians. Math. Program. 141(1-2): 319-348 (2013) - 2012
- [j26]Jonathan Eckstein, Noam Goldberg:
An Improved Branch-and-Bound Method for Maximum Monomial Agreement. INFORMS J. Comput. 24(2): 328-341 (2012) - [j25]Noam Goldberg, Jonathan Eckstein:
Sparse weighted voting classifier selection and its linear programming relaxations. Inf. Process. Lett. 112(12): 481-486 (2012) - 2011
- [j24]Stephen P. Boyd, Neal Parikh, Eric Chu, Borja Peleato, Jonathan Eckstein:
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers. Found. Trends Mach. Learn. 3(1): 1-122 (2011) - 2010
- [j23]Jonathan Eckstein, Paulo J. S. Silva:
Proximal methods for nonlinear programming: double regularization and inexact subproblems. Comput. Optim. Appl. 46(2): 279-304 (2010) - [c2]Noam Goldberg, Jonathan Eckstein:
Boosting Classifiers with Tightened L0-Relaxation Penalties. ICML 2010: 383-390
2000 – 2009
- 2009
- [j22]Jonathan Eckstein, Benar Fux Svaiter:
General Projective Splitting Methods for Sums of Maximal Monotone Operators. SIAM J. Control. Optim. 48(2): 787-811 (2009) - 2008
- [j21]Jonathan Eckstein, Avigdor Gal, Sarit Reiner:
Monitoring an Information Source Under a Politeness Constraint. INFORMS J. Comput. 20(1): 3-20 (2008) - [j20]Farid Alizadeh, Jonathan Eckstein, Nilay Noyan, Gábor Rudolf:
Arrival Rate Approximation by Nonnegative Cubic Splines. Oper. Res. 56(1): 140-156 (2008) - [j19]Jonathan Eckstein, Benar Fux Svaiter:
A family of projective splitting methods for the sum of two maximal monotone operators. Math. Program. 111(1-2): 173-199 (2008) - 2007
- [j18]Jonathan Eckstein, Mikhail Nediak:
Pivot, Cut, and Dive: a heuristic for 0-1 mixed integer programming. J. Heuristics 13(5): 471-503 (2007) - 2006
- [j17]Paulo J. S. Silva, Jonathan Eckstein:
Double-Regularization Proximal Methods, with Complementarity Applications. Comput. Optim. Appl. 33(2-3): 115-156 (2006) - [p2]Cynthia A. Phillips, Jonathan Eckstein, William E. Hart:
Massively Parallel Mixed-Integer Programming: Algorithms and Applications. Parallel Processing for Scientific Computing 2006: 323-340 - 2005
- [j16]Jonathan Eckstein, Mikhail Nediak:
Depth-Optimized Convexity Cuts. Ann. Oper. Res. 139(1): 95-129 (2005) - 2003
- [j15]Jonathan Eckstein:
A practical general approximation criterion for methods of multipliers based on Bregman distances. Math. Program. 96(1): 61-86 (2003) - 2002
- [j14]Jonathan Eckstein, Peter L. Hammer, Ying Liu, Mikhail Nediak, Bruno Simeone:
The Maximum Box Problem and its Application to Data Analysis. Comput. Optim. Appl. 23(3): 285-298 (2002) - 2001
- [j13]Avigdor Gal, Jonathan Eckstein:
Managing periodically updated data in relational databases: a stochastic modeling approach. J. ACM 48(6): 1141-1183 (2001) - [j12]Paulo José da Silva e Silva, Jonathan Eckstein, Carlos Humes Jr.:
Rescaling and Stepsize Selection in Proximal Methods Using Separable Generalized Distances. SIAM J. Optim. 12(1): 238-261 (2001) - 2000
- [i1]Avigdor Gal, Jonathan Eckstein:
Managing Periodically Updated Data in Relational Databases: A Stochastic Modeling Approach. CoRR cs.DB/0007044 (2000)
1990 – 1999
- 1999
- [j11]Jonathan Eckstein, Michael C. Ferris:
Smooth methods of multipliers for complementarity problems. Math. Program. 86(1): 65-90 (1999) - 1998
- [j10]Jonathan Eckstein, Michael C. Ferris:
Operator-Splitting Methods for Monotone Affine Variational Inequalities, with a Parallel Application to Optimal Control. INFORMS J. Comput. 10(2): 218-235 (1998) - [j9]Jonathan Eckstein:
Approximate iterations in Bregman-function-based proximal algorithms. Math. Program. 83: 113-123 (1998) - 1997
- [j8]Jonathan Eckstein:
Distributed versus Centralized Storage and Control for Parallel Branch and Bound: Mixed Integer Programming on the CM-5. Comput. Optim. Appl. 7(2): 199-220 (1997) - [j7]Jonathan Eckstein:
How Much Communication Does Parallel Branch and Bound Need? INFORMS J. Comput. 9(1): 15-29 (1997) - 1996
- [p1]Jonathan Eckstein:
Parallel Branch-and-Bound Methods for Mixed Integer Programming. Applications on Advanced Architecture Computers 1996: 141-153 - 1995
- [j6]Jonathan Eckstein, I. Ilkay Boduroglu, Lazaros C. Polymenakos, Donald Goldfarb:
Data-Parallel Implementations of Dense Simplex Methods on the Connection Machine CM-2. INFORMS J. Comput. 7(4): 402-416 (1995) - 1994
- [j5]Jonathan Eckstein:
Parallel Branch-and-Bound Algorithms for General Mixed Integer Programming on the CM-5. SIAM J. Optim. 4(4): 794-814 (1994) - [c1]Jonathan Eckstein:
Control strategies for parallel mixed integer branch and bound. SC 1994: 41-48 - 1993
- [j4]Jonathan Eckstein:
The Alternating Step Method for Monotropic Programming on the Connection Machine CM-2. INFORMS J. Comput. 5(1): 84-96 (1993) - [j3]Jonathan Eckstein:
Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming. Math. Oper. Res. 18(1): 202-226 (1993) - 1992
- [j2]Jonathan Eckstein, Dimitri P. Bertsekas:
On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators. Math. Program. 55: 293-318 (1992)
1980 – 1989
- 1988
- [j1]Dimitri P. Bertsekas, Jonathan Eckstein:
Dual coordinate step methods for linear network flow problems. Math. Program. 42(1-3): 203-243 (1988)
Coauthor Index
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