101 citations · 488 across the 33 of their papers we have counts for
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A Stochastic Penalty Model for Convex and Nonconvex Optimization with Big Constraints
Konstantin Mishchenko, Peter Richtárik
The last decade witnessed a rise in the importance of supervised learning applications involving {\em big data} and {\em big models}. Big data refers to situations where the amount…
SEGA: Variance Reduction via Gradient Sketching
Filip Hanzely, Konstantin Mishchenko, Peter Richtarik
We propose a randomized first order optimization method--SEGA (SkEtched GrAdient method)-- which progressively throughout its iterations builds a variance-reduced estimate of the g…
A Distributed Flexible Delay-tolerant Proximal Gradient Algorithm
Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick
We develop and analyze an asynchronous algorithm for distributed convex optimization when the objective writes a sum of smooth functions, local to each worker, and a non-smooth fun…