Stochastic Reformulations of Linear Systems: Algorithms and Convergence
Theory

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Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

4 June 2017

Peter Richtárik

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Papers citing "Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory"

15 / 15 papers shown

Title
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Mansel Gower Othmane Sebbouh Nicolas Loizou 95 75 0 18 Jun 2020
Accelerated Gossip via Stochastic Heavy Ball Method Nicolas Loizou Peter Richtárik 44 27 0 23 Sep 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods Nicolas Loizou Peter Richtárik 73 201 0 27 Dec 2017
A New Perspective on Randomized Gossip Algorithms Nicolas Loizou Peter Richtárik 46 30 0 15 Oct 2016
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq ODL 82 99 0 08 Feb 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 135 1,828 0 01 Jul 2014
Stochastic Optimization with Importance Sampling P. Zhao Tong Zhang 96 346 0 13 Jan 2014
Distributed Coordinate Descent Method for Learning with Big Data Peter Richtárik Martin Takáč 191 255 0 08 Oct 2013
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 324 1,250 0 10 Sep 2013
Revisiting Asynchronous Linear Solvers: Provable Convergence Rate Through Randomization H. Avron Alex Druinsky Anshul Gupta 77 91 0 24 Apr 2013
Mini-Batch Primal and Dual Methods for SVMs Martin Takáč A. Bijral Peter Richtárik Nathan Srebro 72 196 0 10 Mar 2013
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 127 487 0 04 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 187 1,033 0 10 Sep 2012
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function Peter Richtárik Martin Takáč 98 772 0 14 Jul 2011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 201 2,274 0 28 Jun 2011

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