Without-Replacement Sampling for Stochastic Gradient Methods:
Convergence Results and Application to Distributed Optimization

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Without-Replacement Sampling for Stochastic Gradient Methods: Convergence Results and Application to Distributed Optimization

2 March 2016

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Papers citing "Without-Replacement Sampling for Stochastic Gradient Methods: Convergence Results and Application to Distributed Optimization"

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Title
Introduction to Online Convex Optimization Elad Hazan OffRL 175 1,932 0 07 Sep 2019
An Introduction to Matrix Concentration Inequalities J. Tropp 168 1,154 0 07 Jan 2015
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 91 353 0 04 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 133 1,826 0 01 Jul 2014
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark Schmidt Francis R. Bach 183 260 0 10 Dec 2012
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 151 574 0 08 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 184 1,033 0 10 Sep 2012
Beneath the valley of the noncommutative arithmetic-geometric mean inequality: conjectures, case-studies, and consequences Benjamin Recht Christopher Ré 64 51 0 19 Feb 2012
A Reliable Effective Terascale Linear Learning System Alekh Agarwal O. Chapelle Miroslav Dudík John Langford 94 418 0 19 Oct 2011
Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter Ohad Shamir Nathan Srebro Karthik Sridharan ODL 120 315 0 22 Jun 2011