Stochastic Variance Reduction for Nonconvex Optimization

19 March 2016

Papers citing "Stochastic Variance Reduction for Nonconvex Optimization"

50 / 111 papers shown

Title
Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach Yingying Li Yujie Tang Runyu Zhang Na Li 21 101 0 19 Dec 2019
Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size Ke Ma Jinshan Zeng Qianqian Xu Xiaochun Cao Wei Liu Yuan Yao 28 3 0 01 Dec 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 32 27 0 28 Oct 2019
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms Kaiyi Ji Zhe Wang Bowen Weng Yi Zhou Wei Zhang Yingbin Liang ODL 18 5 0 21 Oct 2019
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction Pan Xu F. Gao Quanquan Gu 31 83 0 18 Sep 2019
Stochastic AUC Maximization with Deep Neural Networks Mingrui Liu Zhuoning Yuan Yiming Ying Tianbao Yang 17 103 0 28 Aug 2019
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization Stefan Vlaski Ali H. Sayed ODL 29 21 0 19 Aug 2019
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization Digvijay Boob Qi Deng Guanghui Lan 52 92 0 07 Aug 2019
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I Sandeep Kumar K. Rajawat Daniel P. Palomar 19 4 0 21 Jul 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 37 185 0 05 Jun 2019
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias Christopher Aicher N. Foti E. Fox MQ 24 32 0 17 May 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 19 33 0 01 May 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel F. Fleuret Simon Lacoste-Julien 25 134 0 18 Apr 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 28 980 0 01 Apr 2019
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning Aaron Defazio Léon Bottou UQCV DRL 23 112 0 11 Dec 2018
Stagewise Training Accelerates Convergence of Testing Error Over SGD Zhuoning Yuan Yan Yan Rong Jin Tianbao Yang 60 11 0 10 Dec 2018
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence Yi Tian Xu Qi Qi Qihang Lin Rong Jin Tianbao Yang 37 41 0 28 Nov 2018
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate J.N. Zhang Hongyi Zhang S. Sra 26 39 0 10 Nov 2018
SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms Zhe Wang Kaiyi Ji Yi Zhou Yingbin Liang Vahid Tarokh ODL 35 81 0 25 Oct 2018
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD Marten van Dijk Lam M. Nguyen Phuong Ha Nguyen Dzung Phan 36 6 0 09 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 19 31 0 05 Oct 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 15 107 0 04 Oct 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 50 570 0 04 Jul 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks Jinghui Chen Dongruo Zhou Yiqi Tang Ziyan Yang Yuan Cao Quanquan Gu ODL 19 193 0 18 Jun 2018
Stochastic Variance-Reduced Policy Gradient Matteo Papini Damiano Binaghi Giuseppe Canonaco Matteo Pirotta Marcello Restelli 19 174 0 14 Jun 2018
Towards Riemannian Accelerated Gradient Methods Hongyi Zhang S. Sra 16 53 0 07 Jun 2018
Stochastic Zeroth-order Optimization via Variance Reduction method L. Liu Minhao Cheng Cho-Jui Hsieh Dacheng Tao 24 19 0 30 May 2018
Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning Xin Zhang Jia-Wei Liu Zhengyuan Zhu 16 17 0 24 May 2018
Analysis of nonsmooth stochastic approximation: the differential inclusion approach Szymon Majewski B. Miasojedow Eric Moulines 19 49 0 04 May 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 69 1,410 0 24 Mar 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
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien 16 70 0 11 Jan 2018
Neon2: Finding Local Minima via First-Order Oracles Zeyuan Allen-Zhu Yuanzhi Li 21 130 0 17 Nov 2017
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 28 245 0 29 Aug 2017
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization Pan Xu Jinghui Chen Difan Zou Quanquan Gu 31 200 0 20 Jul 2017
A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints Bin Hu Peter M. Seiler Anders Rantzer 30 35 0 25 Jun 2017
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč 11 94 0 20 May 2017
Sub-sampled Cubic Regularization for Non-convex Optimization Jonas Köhler Aurelien Lucchi 19 164 0 16 May 2017
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization Qunwei Li Yi Zhou Yingbin Liang P. Varshney 21 94 0 14 May 2017
Data-Dependent Stability of Stochastic Gradient Descent Ilja Kuzborskij Christoph H. Lampert MLT 9 165 0 05 Mar 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč ODL 30 597 0 01 Mar 2017
Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter Zeyuan Allen-Zhu 20 80 0 02 Feb 2017
Stochastic Alternating Direction Method of Multipliers with Variance Reduction for Nonconvex Optimization Feihu Huang Songcan Chen Zhaosong Lu 27 14 0 10 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 66 1,878 0 08 Oct 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method Lihua Lei Michael I. Jordan 29 96 0 12 Sep 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,201 0 16 Aug 2016