187 citations · 208 across the 6 of their papers we have counts for
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math.OC2021★ 13 cited
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient
David Applegate, Mateo Díaz, Oliver Hinder +4
We present PDLP, a practical first-order method for linear programming (LP) that can solve to the high levels of accuracy that are expected in traditional LP applications. In addit…
math.OC2021
Optimal Convergence Rates for the Proximal Bundle Method
Mateo Díaz, Benjamin Grimmer
We study convergence rates of the classic proximal bundle method for a variety of nonsmooth convex optimization problems. We show that, without any modification, this algorithm ada…
math.OC2021★ 3 cited
Infeasibility detection with primal-dual hybrid gradient for large-scale linear programming
David Applegate, Mateo Díaz, Haihao Lu +1
We study the problem of detecting infeasibility of large-scale linear programming problems using the primal-dual hybrid gradient method (PDHG) of Chambolle and Pock (2011). The lit…