Distributed optimization and statistical learning via the alternating direction method of multipliers S Boyd, N Parikh, E Chu, B Peleato, J Eckstein Foundations and TrendsŪ in Machine learning 3 (1), 1-122, 2011 | 12099 | 2011 |

On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators J Eckstein, DP Bertsekas Mathematical Programming 55 (1-3), 293-318, 1992 | 2382 | 1992 |

Nonlinear proximal point algorithms using Bregman functions, with applications to convex programming J Eckstein Mathematics of Operations Research 18 (1), 202-226, 1993 | 375 | 1993 |

Splitting methods for monotone operators with applications to parallel optimization J Eckstein Massachusetts Institute of Technology, 1989 | 311 | 1989 |

Augmented Lagrangian and alternating direction methods for convex optimization: A tutorial and some illustrative computational results J Eckstein, W Yao RUTCOR Research Reports 32 (3), 2012 | 220 | 2012 |

Approximate iterations in Bregman-function-based proximal algorithms J Eckstein Mathematical programming 83 (1-3), 113-123, 1998 | 187 | 1998 |

PICO: An object-oriented framework for parallel branch and bound J Eckstein, CA Phillips, WE Hart Studies in Computational Mathematics 8, 219-265, 2001 | 144 | 2001 |

Parallel alternating direction multiplier decomposition of convex programs J Eckstein Journal of Optimization Theory and Applications 80 (1), 39-62, 1994 | 143 | 1994 |

Some reformulations and applications of the alternating direction method of multipliers J Eckstein, M Fukushima Large scale optimization, 115-134, 1994 | 132 | 1994 |

Understanding the convergence of the alternating direction method of multipliers: Theoretical and computational perspectives J Eckstein, W Yao Pac. J. Optim. 11 (4), 619-644, 2015 | 131 | 2015 |

Parallel branch-and-bound algorithms for general mixed integer programming on the CM-5 J Eckstein SIAM Journal on Optimization 4 (4), 794-814, 1994 | 127 | 1994 |

Some saddle-function splitting methods for convex programming J Eckstein Optimization Methods and Software 4 (1), 75-83, 1994 | 120 | 1994 |

Stochastic dedication: Designing fixed income portfolios using massively parallel Benders decomposition RS Hiller, J Eckstein Management Science 39 (11), 1422-1438, 1993 | 117 | 1993 |

Dual coordinate step methods for linear network flow problems DP Bertsekas, J Eckstein Mathematical Programming 42 (1-3), 203-243, 1988 | 114 | 1988 |

Distributed asynchronous relaxation methods for linear network flow problems DP Bertsekas, J Eckstein IFAC Proceedings Volumes 20 (5), 103-114, 1987 | 95 | 1987 |

Operator-splitting methods for monotone affine variational inequalities, with a parallel application to optimal control J Eckstein, MC Ferris INFORMS Journal on Computing 10 (2), 218-235, 1998 | 93 | 1998 |

A family of projective splitting methods for the sum of two maximal monotone operators J Eckstein, BF Svaiter Mathematical Programming 111 (1-2), 173-199, 2008 | 83 | 2008 |

General projective splitting methods for sums of maximal monotone operators J Eckstein, BF Svaiter SIAM Journal on Control and Optimization 48 (2), 787-811, 2009 | 81 | 2009 |

The maximum box problem and its application to data analysis J Eckstein, PL Hammer, Y Liu, M Nediak, B Simeone Computational Optimization and Applications 23 (3), 285-298, 2002 | 78 | 2002 |

Managing periodically updated data in relational databases: A stochastic modeling approach A Gal, J Eckstein Journal of the ACM (JACM) 48 (6), 1141-1183, 2001 | 68 | 2001 |