v1v2 (latest)

Minimizing Finite Sums with the Stochastic Average Gradient

10 September 2013

Mark Schmidt

Nicolas Le Roux

Francis R. Bach

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Papers citing "Minimizing Finite Sums with the Stochastic Average Gradient"

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Title
Sub-Sampled Newton Methods II: Local Convergence Rates Farbod Roosta-Khorasani Michael W. Mahoney 94 84 0 18 Jan 2016
Sub-Sampled Newton Methods I: Globally Convergent Algorithms Farbod Roosta-Khorasani Michael W. Mahoney 109 90 0 18 Jan 2016
Distributed Optimization with Arbitrary Local Solvers Chenxin Ma Jakub Konecný Martin Jaggi Virginia Smith Michael I. Jordan Peter Richtárik Martin Takáč 128 197 0 13 Dec 2015
Active Sampler: Light-weight Accelerator for Complex Data Analytics at Scale Jinyang Gao H. V. Jagadish Beng Chin Ooi 63 18 0 12 Dec 2015
Efficient Distributed SGD with Variance Reduction Soham De Tom Goldstein 84 40 0 09 Dec 2015
Variance Reduction for Distributed Stochastic Gradient Descent Soham De Gavin Taylor Tom Goldstein 37 8 0 05 Dec 2015
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma Murat A. Erdogdu 63 13 0 28 Nov 2015
Fast clustering for scalable statistical analysis on structured images Bertrand Thirion Andrés Hoyos-Idrobo J. Kahn Gaël Varoquaux 30 0 0 16 Nov 2015
Speed learning on the fly Pierre-Yves Massé Yann Ollivier 75 13 0 08 Nov 2015
Dual Free Adaptive Mini-batch SDCA for Empirical Risk Minimization Xi He Martin Takávc 83 1 0 22 Oct 2015
SGD with Variance Reduction beyond Empirical Risk Minimization M. Achab Agathe Guilloux Stéphane Gaïffas Emmanuel Bacry 97 5 0 16 Oct 2015
New Optimisation Methods for Machine Learning Aaron Defazio 84 6 0 09 Oct 2015
Stochastic gradient descent methods for estimation with large data sets Dustin Tran Panos Toulis E. Airoldi 53 14 0 22 Sep 2015
AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization S. Sra Adams Wei Yu Mu Li Alex Smola ODL 74 30 0 20 Aug 2015
Doubly Stochastic Primal-Dual Coordinate Method for Bilinear Saddle-Point Problem Adams Wei Yu Qihang Lin Tianbao Yang 57 7 0 14 Aug 2015
Convergence rates of sub-sampled Newton methods Murat A. Erdogdu Andrea Montanari 108 157 0 12 Aug 2015
Distributed Mini-Batch SDCA Martin Takáč Peter Richtárik Nathan Srebro 87 50 0 29 Jul 2015
A Bayesian Approach for Online Classifier Ensemble Qinxun Bai Henry Lam Stan Sclaroff BDL 57 0 0 08 Jul 2015
An optimal randomized incremental gradient method Guanghui Lan Yi Zhou 157 220 0 08 Jul 2015
Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization Yadong Mu Wei Liu Wei Fan 98 33 0 28 Jun 2015
Splash: User-friendly Programming Interface for Parallelizing Stochastic Algorithms Yuchen Zhang Michael I. Jordan 92 20 0 24 Jun 2015
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 146 196 0 23 Jun 2015
Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems Zhanxing Zhu Amos J. Storkey ODL 141 19 0 12 Jun 2015
Variance Reduced Stochastic Gradient Descent with Neighbors Thomas Hofmann Aurelien Lucchi Simon Lacoste-Julien Brian McWilliams ODL 86 154 0 11 Jun 2015
Accelerated Stochastic Gradient Descent for Minimizing Finite Sums Atsushi Nitanda ODL 108 24 0 09 Jun 2015
Primal Method for ERM with Flexible Mini-batching Schemes and Non-convex Losses Dominik Csiba Peter Richtárik 92 23 0 07 Jun 2015
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives Zeyuan Allen-Zhu Yang Yuan 116 199 0 05 Jun 2015
Efficient Elastic Net Regularization for Sparse Linear Models Zachary Chase Lipton Charles Elkan 68 4 0 24 May 2015
Mind the duality gap: safer rules for the Lasso Olivier Fercoq Alexandre Gramfort Joseph Salmon 132 140 0 13 May 2015
Towards stability and optimality in stochastic gradient descent Panos Toulis Dustin Tran E. Airoldi 102 56 0 10 May 2015
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields Mark Schmidt Reza Babanezhad Mohamed Osama Ahmed Aaron Defazio Ann Clifton Anoop Sarkar 96 83 0 16 Apr 2015
Expectation Propagation in the large-data limit Guillaume P. Dehaene Simon Barthelmé 93 44 0 27 Mar 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 137 97 0 27 Feb 2015
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq ODL 126 99 0 08 Feb 2015
Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM A. Punjani Marcus A. Brubaker 42 3 0 19 Jan 2015
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss Yuchen Zhang Lin Xiao 177 72 0 01 Jan 2015
Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity Zheng Qu Peter Richtárik 83 130 0 27 Dec 2014
Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions Alexandre Défossez Francis R. Bach 108 13 0 29 Nov 2014
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 155 58 0 21 Nov 2014
SelfieBoost: A Boosting Algorithm for Deep Learning Shai Shalev-Shwartz FedML 77 17 0 13 Nov 2014
A Lower Bound for the Optimization of Finite Sums Alekh Agarwal Léon Bottou 191 124 0 02 Oct 2014
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 122 265 0 10 Sep 2014
Global Convergence of Online Limited Memory BFGS Aryan Mokhtari Alejandro Ribeiro 78 164 0 06 Sep 2014
On Data Preconditioning for Regularized Loss Minimization Tianbao Yang Rong Jin Shenghuo Zhu Qihang Lin 161 9 0 13 Aug 2014
Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems Aaron Defazio T. Caetano Justin Domke 115 169 0 10 Jul 2014
A Coordinate Descent Primal-Dual Algorithm and Application to Distributed Asynchronous Optimization Pascal Bianchi W. Hachem F. Iutzeler 150 57 0 03 Jul 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 143 1,830 0 01 Jul 2014
Randomized Block Coordinate Descent for Online and Stochastic Optimization Huahua Wang A. Banerjee ODL 149 36 0 01 Jul 2014
Smoothed Gradients for Stochastic Variational Inference Stephan Mandt David M. Blei BDL DiffM 101 29 0 13 Jun 2014
Peacock: Learning Long-Tail Topic Features for Industrial Applications Yi Wang Xuemin Zhao Zhenlong Sun Hao Yan Lifeng Wang Zhihui Jin Liubin Wang Yang Gao Ching Law Jia Zeng AI4TS 179 61 0 17 May 2014