Minimizing Finite Sums with the Stochastic Average Gradient

10 September 2013

Nicolas Le Roux

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

50 / 504 papers shown

Title
Asynchronous Stochastic Block Coordinate Descent with Variance Reduction Bin Gu Zhouyuan Huo Heng-Chiao Huang 23 10 0 29 Oct 2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes Soham De A. Yadav David Jacobs Tom Goldstein ODL 37 62 0 18 Oct 2016
Analysis and Implementation of an Asynchronous Optimization Algorithm for the Parameter Server Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson 31 54 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 71 1,877 0 08 Oct 2016
Understanding intermediate layers using linear classifier probes Guillaume Alain Yoshua Bengio FAtt 53 900 0 05 Oct 2016
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 47 36 0 04 Oct 2016
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration Hongzhou Lin Julien Mairal Zaïd Harchaoui 31 13 0 04 Oct 2016
A Primer on Coordinate Descent Algorithms Hao-Jun Michael Shi Shenyinying Tu Yangyang Xu W. Yin 40 90 0 30 Sep 2016
Data Dependent Convergence for Distributed Stochastic Optimization A. Bijral 17 0 0 30 Aug 2016
AIDE: Fast and Communication Efficient Distributed Optimization Sashank J. Reddi Jakub Konecný Peter Richtárik Barnabás Póczós Alex Smola 19 150 0 24 Aug 2016
Fast and Simple Optimization for Poisson Likelihood Models Niao He Zaïd Harchaoui Yichen Wang Le Song 23 14 0 03 Aug 2016
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 21 139 0 27 Jul 2016
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning Aryan Mokhtari Alec Koppel Alejandro Ribeiro 24 14 0 15 Jun 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 111 3,178 0 15 Jun 2016
ASAGA: Asynchronous Parallel SAGA Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien AI4TS 29 101 0 15 Jun 2016
On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression Kobi Cohen A. Nedić R. Srikant 23 44 0 09 Jun 2016
Variance-Reduced Proximal Stochastic Gradient Descent for Non-convex Composite optimization Xiyu Yu Dacheng Tao 27 5 0 02 Jun 2016
Distributed Asynchronous Dual Free Stochastic Dual Coordinate Ascent Zhouyuan Huo Heng-Chiao Huang 14 1 0 29 May 2016
Level Up Your Strategy: Towards a Descriptive Framework for Meaningful Enterprise Gamification Xinghao Pan 29 62 0 29 May 2016
Stochastic Optimization for Large-scale Optimal Transport Aude Genevay Marco Cuturi Gabriel Peyré Francis R. Bach OT 16 460 0 27 May 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin Raffaello Camoriano Lorenzo Rosasco 17 70 0 26 May 2016
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 36 185 0 25 May 2016
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization Davood Hajinezhad Mingyi Hong T. Zhao Zhaoran Wang 24 45 0 25 May 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 36 240 0 23 May 2016
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 23 54 0 23 May 2016
A Multi-Batch L-BFGS Method for Machine Learning A. Berahas J. Nocedal Martin Takáč ODL 24 110 0 19 May 2016
On the Iteration Complexity of Oblivious First-Order Optimization Algorithms Yossi Arjevani Ohad Shamir 26 33 0 11 May 2016
Empirical study of PROXTONE and PROXTONE $^+$ for Fast Learning of Large Scale Sparse Models Ziqiang Shi Rujie Liu 36 0 0 18 Apr 2016
Algorithms for stochastic optimization with functional or expectation constraints Guanghui Lan Zhiqiang Zhou 20 50 0 13 Apr 2016
Asynchronous Stochastic Gradient Descent with Variance Reduction for Non-Convex Optimization Zhouyuan Huo Heng-Chiao Huang 25 48 0 12 Apr 2016
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis Weiran Wang Jialei Wang Dan Garber Nathan Srebro 30 31 0 07 Apr 2016
Doubly Random Parallel Stochastic Methods for Large Scale Learning Aryan Mokhtari Alec Koppel Alejandro Ribeiro 12 15 0 22 Mar 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 50 597 0 19 Mar 2016
Fast Incremental Method for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 33 44 0 19 Mar 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 32 577 0 18 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 27 390 0 17 Mar 2016
Optimal Black-Box Reductions Between Optimization Objectives Zeyuan Allen-Zhu Elad Hazan 19 96 0 17 Mar 2016
Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing Chenxin Ma Martin Takáč 28 10 0 16 Mar 2016
Starting Small -- Learning with Adaptive Sample Sizes Hadi Daneshmand Aurelien Lucchi Thomas Hofmann 34 0 0 09 Mar 2016
Stochastic dual averaging methods using variance reduction techniques for regularized empirical risk minimization problems Tomoya Murata Taiji Suzuki 16 3 0 08 Mar 2016
Fast Nonsmooth Regularized Risk Minimization with Continuation Shuai Zheng Ruiliang Zhang James T. Kwok 23 1 0 25 Feb 2016
Loss factorization, weakly supervised learning and label noise robustness Giorgio Patrini Frank Nielsen Richard Nock M. Carioni NoLa 24 112 0 08 Feb 2016
A Simple Practical Accelerated Method for Finite Sums Aaron Defazio 30 121 0 08 Feb 2016
Hyperparameter optimization with approximate gradient Fabian Pedregosa 40 442 0 07 Feb 2016
Importance Sampling for Minibatches Dominik Csiba Peter Richtárik 32 113 0 06 Feb 2016
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters Zeyuan Allen-Zhu Yang Yuan Karthik Sridharan 15 27 0 05 Feb 2016
Reducing Runtime by Recycling Samples Jialei Wang Hai Wang Nathan Srebro 40 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 24 16 0 30 Jan 2016
Sub-Sampled Newton Methods II: Local Convergence Rates Farbod Roosta-Khorasani Michael W. Mahoney 33 84 0 18 Jan 2016
Sub-Sampled Newton Methods I: Globally Convergent Algorithms Farbod Roosta-Khorasani Michael W. Mahoney 25 89 0 18 Jan 2016