v1v2 (latest)

Minimizing Finite Sums with the Stochastic Average Gradient

10 September 2013

Mark Schmidt

Nicolas Le Roux

Francis R. Bach

ArXiv (abs)PDF HTML

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

50 / 506 papers shown

Title
Finding Approximate Local Minima Faster than Gradient Descent Naman Agarwal Zeyuan Allen-Zhu Brian Bullins Elad Hazan Tengyu Ma 136 83 0 03 Nov 2016
Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate Aryan Mokhtari Mert Gurbuzbalaban Alejandro Ribeiro 147 37 0 01 Nov 2016
Asynchronous Stochastic Block Coordinate Descent with Variance Reduction Bin Gu Zhouyuan Huo Heng-Chiao Huang 79 10 0 29 Oct 2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes Soham De A. Yadav David Jacobs Tom Goldstein ODL 177 62 0 18 Oct 2016
Analysis and Implementation of an Asynchronous Optimization Algorithm for the Parameter Server Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson 146 54 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 154 1,912 0 08 Oct 2016
Understanding intermediate layers using linear classifier probes Guillaume Alain Yoshua Bengio FAtt 175 957 0 05 Oct 2016
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 207 36 0 04 Oct 2016
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration Hongzhou Lin Julien Mairal Zaïd Harchaoui 90 13 0 04 Oct 2016
A Primer on Coordinate Descent Algorithms Hao-Jun Michael Shi Shenyinying Tu Yangyang Xu W. Yin 91 89 0 30 Sep 2016
Data Dependent Convergence for Distributed Stochastic Optimization A. Bijral 19 0 0 30 Aug 2016
AIDE: Fast and Communication Efficient Distributed Optimization Sashank J. Reddi Jakub Konecný Peter Richtárik Barnabás Póczós Alex Smola 73 150 0 24 Aug 2016
Fast and Simple Optimization for Poisson Likelihood Models Niao He Zaïd Harchaoui Yichen Wang Le Song 102 14 0 03 Aug 2016
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 90 140 0 27 Jul 2016
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning Aryan Mokhtari Alec Koppel Alejandro Ribeiro 71 14 0 15 Jun 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 274 3,228 0 15 Jun 2016
ASAGA: Asynchronous Parallel SAGA Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien AI4TS 87 101 0 15 Jun 2016
On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression Kobi Cohen A. Nedić R. Srikant 72 43 0 09 Jun 2016
Variance-Reduced Proximal Stochastic Gradient Descent for Non-convex Composite optimization Xiyu Yu Dacheng Tao 62 5 0 02 Jun 2016
Distributed Asynchronous Dual Free Stochastic Dual Coordinate Ascent Zhouyuan Huo Heng-Chiao Huang 31 1 0 29 May 2016
Level Up Your Strategy: Towards a Descriptive Framework for Meaningful Enterprise Gamification Xinghao Pan 73 63 0 29 May 2016
Stochastic Optimization for Large-scale Optimal Transport Aude Genevay Marco Cuturi Gabriel Peyré Francis R. Bach OT 87 469 0 27 May 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin Raffaello Camoriano Lorenzo Rosasco 79 70 0 26 May 2016
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 151 185 0 25 May 2016
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization Davood Hajinezhad Mingyi Hong T. Zhao Zhaoran Wang 83 45 0 25 May 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 117 241 0 23 May 2016
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 107 54 0 23 May 2016
A Multi-Batch L-BFGS Method for Machine Learning A. Berahas J. Nocedal Martin Takáč ODL 106 112 0 19 May 2016
On the Iteration Complexity of Oblivious First-Order Optimization Algorithms Yossi Arjevani Ohad Shamir 82 33 0 11 May 2016
Empirical study of PROXTONE and PROXTONE $^+$ for Fast Learning of Large Scale Sparse Models Ziqiang Shi Rujie Liu 45 0 0 18 Apr 2016
Algorithms for stochastic optimization with functional or expectation constraints Guanghui Lan Zhiqiang Zhou 75 50 0 13 Apr 2016
Asynchronous Stochastic Gradient Descent with Variance Reduction for Non-Convex Optimization Zhouyuan Huo Heng-Chiao Huang 95 49 0 12 Apr 2016
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis Weiran Wang Jialei Wang Dan Garber Nathan Srebro 93 31 0 07 Apr 2016
Doubly Random Parallel Stochastic Methods for Large Scale Learning Aryan Mokhtari Alec Koppel Alejandro Ribeiro 39 15 0 22 Mar 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 127 604 0 19 Mar 2016
Fast Incremental Method for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 95 44 0 19 Mar 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 138 582 0 18 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 127 392 0 17 Mar 2016
Optimal Black-Box Reductions Between Optimization Objectives Zeyuan Allen-Zhu Elad Hazan 111 96 0 17 Mar 2016
Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing Chenxin Ma Martin Takáč 83 10 0 16 Mar 2016
Starting Small -- Learning with Adaptive Sample Sizes Hadi Daneshmand Aurelien Lucchi Thomas Hofmann 46 0 0 09 Mar 2016
Stochastic dual averaging methods using variance reduction techniques for regularized empirical risk minimization problems Tomoya Murata Taiji Suzuki 33 3 0 08 Mar 2016
Fast Nonsmooth Regularized Risk Minimization with Continuation Shuai Zheng Ruiliang Zhang James T. Kwok 42 1 0 25 Feb 2016
Loss factorization, weakly supervised learning and label noise robustness Giorgio Patrini Frank Nielsen Richard Nock M. Carioni NoLa 194 114 0 08 Feb 2016
A Simple Practical Accelerated Method for Finite Sums Aaron Defazio 155 121 0 08 Feb 2016
Hyperparameter optimization with approximate gradient Fabian Pedregosa 181 451 0 07 Feb 2016
Importance Sampling for Minibatches Dominik Csiba Peter Richtárik 111 117 0 06 Feb 2016
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters Zeyuan Allen-Zhu Yang Yuan Karthik Sridharan 102 28 0 05 Feb 2016
Reducing Runtime by Recycling Samples Jialei Wang Hai Wang Nathan Srebro 63 3 0 05 Feb 2016
SCOPE: Scalable Composite Optimization for Learning on Spark Shen-Yi Zhao Ru Xiang Yinghuan Shi Peng Gao Wu-Jun Li 124 16 0 30 Jan 2016