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

2 March 2016

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

8 / 8 papers shown

Title
Introduction to Online Convex Optimization Elad Hazan OffRL 121 1,922 0 07 Sep 2019
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 72 353 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 115 1,817 0 01 Jul 2014
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 143 573 0 08 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 138 1,031 0 10 Sep 2012
Beneath the valley of the noncommutative arithmetic-geometric mean inequality: conjectures, case-studies, and consequences Benjamin Recht Christopher Ré 49 51 0 19 Feb 2012
A Reliable Effective Terascale Linear Learning System Alekh Agarwal O. Chapelle Miroslav Dudík John Langford 88 418 0 19 Oct 2011
Better Mini-Batch Algorithms via Accelerated Gradient Methods Andrew Cotter Ohad Shamir Nathan Srebro Karthik Sridharan ODL 111 313 0 22 Jun 2011