Stochastic Variance Reduction for Nonconvex Optimization

19 March 2016

Papers citing "Stochastic Variance Reduction for Nonconvex Optimization"

50 / 124 papers shown

Title
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 58 1,395 0 29 Feb 2020
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems Junchi Yang Negar Kiyavash Niao He 30 83 0 22 Feb 2020
A Unified Convergence Analysis for Shuffling-Type Gradient Methods Lam M. Nguyen Quoc Tran-Dinh Dzung Phan Phuong Ha Nguyen Marten van Dijk 39 78 0 19 Feb 2020
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 57 30 0 13 Feb 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 40 17 0 11 Feb 2020
Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach Yingying Li Yujie Tang Runyu Zhang Na Li 24 101 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 36 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 33 83 0 18 Sep 2019
Stochastic AUC Maximization with Deep Neural Networks Mingrui Liu Zhuoning Yuan Yiming Ying Tianbao Yang 27 103 0 28 Aug 2019
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization Stefan Vlaski Ali H. Sayed ODL 37 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 32 4 0 21 Jul 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 39 186 0 05 Jun 2019
An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient Pan Xu F. Gao Quanquan Gu 21 93 0 29 May 2019
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 43 397 0 24 May 2019
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias Christopher Aicher N. Foti E. Fox MQ 32 32 0 17 May 2019
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time Y. Lee Zhao Song Qiuyi Zhang 24 115 0 11 May 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 19 34 0 01 May 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel François Fleuret Simon Lacoste-Julien 25 135 0 18 Apr 2019
On the Adaptivity of Stochastic Gradient-Based Optimization Lihua Lei Michael I. Jordan ODL 24 22 0 09 Apr 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 21 101 0 02 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 28 985 0 01 Apr 2019
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate Lijun Zhang Zhi-Hua Zhou 22 29 0 27 Jan 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 50 571 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 21 174 0 14 Jun 2018
Towards Riemannian Accelerated Gradient Methods Hongyi Zhang S. Sra 21 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 21 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 1,412 0 24 Mar 2018
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization Zhe Wang Yi Zhou Yingbin Liang Guanghui Lan 35 47 0 20 Feb 2018
Differentially Private Empirical Risk Minimization Revisited: Faster and More General Di Wang Minwei Ye Jinhui Xu 26 268 0 14 Feb 2018
Stochastic Variance-Reduced Hamilton Monte Carlo Methods Difan Zou Pan Xu Quanquan Gu BDL 37 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 49 52 0 12 Feb 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods Rémi Leblond Fabian Pedregosa Simon Lacoste-Julien 21 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