A Proximal Stochastic Gradient Method with Progressive Variance Reduction

19 March 2014

Tong Zhang

Papers citing "A Proximal Stochastic Gradient Method with Progressive Variance Reduction"

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Title
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization Feihu Huang Bin Gu Zhouyuan Huo Songcan Chen Heng-Chiao Huang 12 26 0 16 Feb 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 11 139 0 15 Feb 2019
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence Yi Tian Xu Qi Qi Qihang Lin R. L. Jin Tianbao Yang 37 40 0 28 Nov 2018
First-order Newton-type Estimator for Distributed Estimation and Inference Xi Chen Weidong Liu Yichen Zhang 30 48 0 28 Nov 2018
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate Junzhe Zhang Hongyi Zhang S. Sra 21 39 0 10 Nov 2018
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates Kaiwen Zhou Fanhua Shang James Cheng 14 74 0 28 Jun 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Analysis of nonsmooth stochastic approximation: the differential inclusion approach Szymon Majewski B. Miasojedow Eric Moulines 11 49 0 04 May 2018
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization Zhe Wang Yi Zhou Yingbin Liang Guanghui Lan 35 46 0 20 Feb 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 27 31 0 13 Feb 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 39 116 0 13 Feb 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 44 52 0 12 Feb 2018
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity S. Du Wei Hu 58 120 0 05 Feb 2018
ConvSCCS: convolutional self-controlled case series model for lagged adverse event detection Maryan Morel Emmanuel Bacry Stéphane Gaïffas Agathe Guilloux F. Leroy 19 14 0 21 Dec 2017
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 28 245 0 29 Aug 2017
An inexact subsampled proximal Newton-type method for large-scale machine learning Xuanqing Liu Cho-Jui Hsieh J. Lee Yuekai Sun 27 15 0 28 Aug 2017
Variance-Reduced Stochastic Learning under Random Reshuffling Bicheng Ying Kun Yuan Ali H. Sayed 25 13 0 04 Aug 2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization Tomoya Murata Taiji Suzuki OffRL 33 28 0 01 Mar 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč ODL 28 596 0 01 Mar 2017
Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox Jialei Wang Weiran Wang Nathan Srebro 16 54 0 21 Feb 2017
Asynchronous Stochastic Block Coordinate Descent with Variance Reduction Bin Gu Zhouyuan Huo Heng-Chiao Huang 23 10 0 29 Oct 2016
Analysis and Implementation of an Asynchronous Optimization Algorithm for the Parameter Server Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson 16 54 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 45 1,876 0 08 Oct 2016
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure A. Bietti Julien Mairal 44 36 0 04 Oct 2016
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration Hongzhou Lin Julien Mairal Zaïd Harchaoui 25 13 0 04 Oct 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method Lihua Lei Michael I. Jordan 23 96 0 12 Sep 2016
Convexified Convolutional Neural Networks Yuchen Zhang Percy Liang Martin J. Wainwright 24 64 0 04 Sep 2016
Stochastic Frank-Wolfe Methods for Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 18 138 0 27 Jul 2016
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization Tianlin Li Shiqian Ma D. Goldfarb Wei Liu 21 176 0 05 Jul 2016
AdaNet: Adaptive Structural Learning of Artificial Neural Networks Corinna Cortes X. Gonzalvo Vitaly Kuznetsov M. Mohri Scott Yang 29 282 0 05 Jul 2016
Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition Yi Tian Xu Qihang Lin Tianbao Yang 28 11 0 04 Jul 2016
Variance-Reduced Proximal Stochastic Gradient Descent for Non-convex Composite optimization Xiyu Yu Dacheng Tao 19 5 0 02 Jun 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy Aryan Mokhtari Alejandro Ribeiro ODL 14 32 0 24 May 2016
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 22 239 0 23 May 2016
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 17 54 0 23 May 2016
Accelerated Randomized Mirror Descent Algorithms For Composite Non-strongly Convex Optimization L. Hien Cuong V Nguyen Huan Xu Canyi Lu Jiashi Feng 20 19 0 23 May 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems B. Palaniappan Francis R. Bach 18 210 0 20 May 2016
Barzilai-Borwein Step Size for Stochastic Gradient Descent Conghui Tan Shiqian Ma Yuhong Dai Yuqiu Qian 40 182 0 13 May 2016
Stochastic Variance-Reduced ADMM Shuai Zheng James T. Kwok 44 59 0 24 Apr 2016
Trading-off variance and complexity in stochastic gradient descent Vatsal Shah Megasthenis Asteris Anastasios Kyrillidis Sujay Sanghavi 19 13 0 22 Mar 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 575 0 18 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 16 390 0 17 Mar 2016
Kalman-based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning V. Patel 15 35 0 03 Dec 2015
Stochastic modified equations and adaptive stochastic gradient algorithms Qianxiao Li Cheng Tai E. Weinan 30 279 0 19 Nov 2015
Stop Wasting My Gradients: Practical SVRG Reza Babanezhad Mohamed Osama Ahmed Alim Virani Mark W. Schmidt Jakub Konecný Scott Sallinen 8 134 0 05 Nov 2015
New Optimisation Methods for Machine Learning Aaron Defazio 41 6 0 09 Oct 2015
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 38 194 0 23 Jun 2015
Towards stability and optimality in stochastic gradient descent Panos Toulis Dustin Tran E. Airoldi 16 56 0 10 May 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 25 273 0 16 Apr 2015
Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields Mark W. Schmidt Reza Babanezhad Mohamed Osama Ahmed Aaron Defazio Ann Clifton Anoop Sarkar 35 83 0 16 Apr 2015