20 citations · 79 across the 8 of their papers we have counts for
9 papers
Stochastic Projective Splitting: Solving Saddle-Point Problems with Multiple Regularizers
Patrick R. Johnstone, Jonathan Eckstein, Thomas Flynn +1
We present a new, stochastic variant of the projective splitting (PS) family of algorithms for monotone inclusion problems. It can solve min-max and noncooperative game formulation…
Single-Forward-Step Projective Splitting: Exploiting Cocoercivity
Patrick R. Johnstone, Jonathan Eckstein
This work describes a new variant of projective splitting for solving maximal monotone inclusions and complicated convex optimization problems. In the new version, cocoercive opera…
Projective Splitting with Forward Steps only Requires Continuity
Patrick R. Johnstone, Jonathan Eckstein
A recent innovation in projective splitting algorithms for monotone operator inclusions has been the development of a procedure using two forward steps instead of the customary pro…
Convergence Rates for Projective Splitting
Patrick R. Johnstone, Jonathan Eckstein
Projective splitting is a family of methods for solving inclusions involving sums of maximal monotone operators. First introduced by Eckstein and Svaiter in 2008, these methods hav…
Projective Splitting with Forward Steps: Asynchronous and Block-Iterative Operator Splitting
Patrick R. Johnstone, Jonathan Eckstein
This work is concerned with the classical problem of finding a zero of a sum of maximal monotone operators. For the projective splitting framework recently proposed by Combettes an…
Faster Subgradient Methods for Functions with Hölderian Growth
Patrick R. Johnstone, Pierre Moulin
The purpose of this manuscript is to derive new convergence results for several subgradient methods applied to minimizing nonsmooth convex functions with Hölderian growth. The grow…