Dual coordinate step methods for linear network flow problems. - Dimitri P. Bertsekas; Jonathan Eckstein (Math. Program., 1988)

On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators. - Jonathan Eckstein; Dimitri P. Bertsekas (Math. Program., 1992)

The Alternating Step Method for Monotropic Programming on the Connection Machine CM-2. - Jonathan Eckstein (INFORMS J. Comput., 1993)

Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming. - Jonathan Eckstein (Math. Oper. Res., 1993)

Control strategies for parallel mixed integer branch and bound. - Jonathan Eckstein (SC, 1994)

Parallel Branch-and-Bound Algorithms for General Mixed Integer Programming on the CM-5. - Jonathan Eckstein (SIAM J. Optim., 1994)

Data-Parallel Implementations of Dense Simplex Methods on the Connection Machine CM-2. - Jonathan Eckstein; I. Ilkay Boduroglu; Lazaros C. Polymenakos; Donald Goldfarb (INFORMS J. Comput., 1995)

Parallel Branch-and-Bound Methods for Mixed Integer Programming. - Jonathan Eckstein (Applications on Advanced Architecture Computers, 1996)

Distributed versus Centralized Storage and Control for Parallel Branch and Bound: Mixed Integer Programming on the CM-5. - Jonathan Eckstein (Comput. Optim. Appl., 1997)

How Much Communication Does Parallel Branch and Bound Need? - Jonathan Eckstein (INFORMS J. Comput., 1997)

Operator-Splitting Methods for Monotone Affine Variational Inequalities, with a Parallel Application to Optimal Control. - Jonathan Eckstein; Michael C. Ferris (INFORMS J. Comput., 1998)

Approximate iterations in Bregman-function-based proximal algorithms. - Jonathan Eckstein (Math. Program., 1998)

Smooth methods of multipliers for complementarity problems. - Jonathan Eckstein; Michael C. Ferris (Math. Program., 1999)

Managing periodically updated data in relational databases: a stochastic modeling approach. - Avigdor Gal; Jonathan Eckstein (J. ACM, 2001)

Rescaling and Stepsize Selection in Proximal Methods Using Separable Generalized Distances. - Paulo José da Silva e Silva; Jonathan Eckstein; Carlos Humes Jr. (SIAM J. Optim., 2001)

The Maximum Box Problem and its Application to Data Analysis. - Jonathan Eckstein; Peter L. Hammer; Ying Liu; Mikhail Nediak; Bruno Simeone (Comput. Optim. Appl., 2002)

A practical general approximation criterion for methods of multipliers based on Bregman distances. - Jonathan Eckstein (Math. Program., 2003)

Depth-Optimized Convexity Cuts. - Jonathan Eckstein; Mikhail Nediak (Ann. Oper. Res., 2005)

Massively Parallel Mixed-Integer Programming: Algorithms and Applications. - Cynthia A. Phillips; Jonathan Eckstein; William E. Hart (Parallel Processing for Scientific Computing, 2006)

Double-Regularization Proximal Methods, with Complementarity Applications. - Paulo J. S. Silva; Jonathan Eckstein (Comput. Optim. Appl., 2006)

Pivot, Cut, and Dive: a heuristic for 0-1 mixed integer programming. - Jonathan Eckstein; Mikhail Nediak (J. Heuristics, 2007)

Monitoring an Information Source Under a Politeness Constraint. - Jonathan Eckstein; Avigdor Gal; Sarit Reiner (INFORMS J. Comput., 2008)

Arrival Rate Approximation by Nonnegative Cubic Splines. - Farid Alizadeh; Jonathan Eckstein; Nilay Noyan; Gábor Rudolf (Oper. Res., 2008)

A family of projective splitting methods for the sum of two maximal monotone operators. - Jonathan Eckstein; Benar Fux Svaiter (Math. Program., 2008)

General Projective Splitting Methods for Sums of Maximal Monotone Operators. - Jonathan Eckstein; Benar Fux Svaiter (SIAM J. Control. Optim., 2009)

Boosting Classifiers with Tightened L0-Relaxation Penalties. - Noam Goldberg; Jonathan Eckstein (ICML, 2010)

Proximal methods for nonlinear programming: double regularization and inexact subproblems. - Jonathan Eckstein; Paulo J. S. Silva (Comput. Optim. Appl., 2010)

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers. - Stephen P. Boyd; Neal Parikh; Eric Chu; Borja Peleato; Jonathan Eckstein (Found. Trends Mach. Learn., 2011)

An Improved Branch-and-Bound Method for Maximum Monomial Agreement. - Jonathan Eckstein; Noam Goldberg (INFORMS J. Comput., 2012)

Sparse weighted voting classifier selection and its linear programming relaxations. - Noam Goldberg; Jonathan Eckstein (Inf. Process. Lett., 2012)

A practical relative error criterion for augmented Lagrangians. - Jonathan Eckstein; Paulo J. S. Silva (Math. Program., 2013)

PEBBL: an object-oriented framework for scalable parallel branch and bound. - Jonathan Eckstein; William E. Hart; Cynthia A. Phillips (Math. Program. Comput., 2015)

Multilevel Optimization Modeling for Risk-Averse Stochastic Programming. - Jonathan Eckstein; Deniz Eskandani; Jingnan Fan (INFORMS J. Comput., 2016)

Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement. - Jonathan Eckstein; Noam Goldberg; Ai Kagawa (ICML, 2017)

Approximate ADMM algorithms derived from Lagrangian splitting. - Jonathan Eckstein; Wang Yao (Comput. Optim. Appl., 2017)

A Simplified Form of Block-Iterative Operator Splitting and an Asynchronous Algorithm Resembling the Multi-Block Alternating Direction Method of Multipliers. - Jonathan Eckstein (J. Optim. Theory Appl., 2017)

Projective Splitting with Forward Steps: Asynchronous and Block-Iterative Operator Splitting. - Patrick R. Johnstone; Jonathan Eckstein (CoRR, 2018)

Efficient Distributed-Memory Parallel Matrix-Vector Multiplication with Wide or Tall Unstructured Sparse Matrices. - Jonathan Eckstein; Gyorgy Matyasfalvi (CoRR, 2018)

Comments on a Simplified Form of Block-Iterative Operator Splitting, and an Asynchronous Algorithm Resembling the Multi-block Alternating Direction Method of Multipliers. - Jonathan Eckstein (J. Optim. Theory Appl., 2018)

Asynchronous block-iterative primal-dual decomposition methods for monotone inclusions. - Patrick L. Combettes; Jonathan Eckstein (Math. Program., 2018)

Relative-error approximate versions of Douglas-Rachford splitting and special cases of the ADMM. - Jonathan Eckstein; Wang Yao (Math. Program., 2018)

Convergence Rates for Projective Splitting. - Patrick R. Johnstone; Jonathan Eckstein (SIAM J. Optim., 2019)

REPR: Rule-Enhanced Penalized Regression. - Jonathan Eckstein; Ai Kagawa; Noam Goldberg (INFORMS J. Optim., 2019)

Relative-error inertial-relaxed inexact versions of Douglas-Rachford and ADMM splitting algorithms. - Maicon Marques Alves; Jonathan Eckstein; Marina Geremia; Jefferson G. Melo (Comput. Optim. Appl., 2020)

Deriving solution value bounds from the ADMM. - Jonathan Eckstein (Optim. Lett., 2020)

Projective splitting with forward steps only requires continuity. - Patrick R. Johnstone; Jonathan Eckstein (Optim. Lett., 2020)

Single-forward-step projective splitting: exploiting cocoercivity. - Patrick R. Johnstone; Jonathan Eckstein (Comput. Optim. Appl., 2021)

Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers. - Patrick R. Johnstone; Jonathan Eckstein; Thomas Flynn 001; Shinjae Yoo (CoRR, 2021)

Projective splitting with forward steps. - Patrick R. Johnstone; Jonathan Eckstein (Math. Program., 2022)

Stochastic projective splitting. - Patrick R. Johnstone; Jonathan Eckstein; Thomas Flynn 001; Shinjae Yoo (Comput. Optim. Appl., 2024)

Correction to: Stochastic projective splitting. - Patrick R. Johnstone; Jonathan Eckstein; Thomas Flynn 001; Shinjae Yoo (Comput. Optim. Appl., 2024)

Projective Hedging Algorithms for Multistage Stochastic Programming, Supporting Distributed and Asynchronous Implementation. - Jonathan Eckstein; Jean-Paul Watson; David L. Woodruff (Oper. Res., 2025)