A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization

13 February 2018

Papers citing "A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization"

20 / 20 papers shown

Title
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems Yanjie Zhong Jiaqi Li Soumendra Lahiri 22 1 0 29 Jan 2024
Convergence of Nonconvex PnP-ADMM with MMSE Denoisers Chicago Park S. Shoushtari Weijie Gan Ulugbek S. Kamilov 10 0 0 30 Nov 2023
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 25 1 0 09 Nov 2023
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 26 0 0 19 Oct 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 46 6 0 02 Jan 2023
Distributed Policy Gradient with Variance Reduction in Multi-Agent Reinforcement Learning Xiaoxiao Zhao Jinlong Lei Li Li Jie-bin Chen OffRL 18 2 0 25 Nov 2021
Distributed stochastic proximal algorithm with random reshuffling for non-smooth finite-sum optimization Xia Jiang Xianlin Zeng Jian Sun Jie Chen Lihua Xie 13 6 0 06 Nov 2021
Provably Faster Algorithms for Bilevel Optimization Junjie Yang Kaiyi Ji Yingbin Liang 41 132 0 08 Jun 2021
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity Shaocong Ma Ziyi Chen Yi Zhou Shaofeng Zou 15 11 0 30 Mar 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 33 14 0 21 Mar 2021
Variance Reduced Training with Stratified Sampling for Forecasting Models Yucheng Lu Youngsuk Park Lifan Chen Bernie Wang Christopher De Sa Dean Phillips Foster AI4TS 30 17 0 02 Mar 2021
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 24 125 0 25 Aug 2020
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 55 30 0 13 Feb 2020
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms Kaiyi Ji Zhe Wang Bowen Weng Yi Zhou Wei Zhang Yingbin Liang ODL 13 5 0 21 Oct 2019
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction Pan Xu F. Gao Quanquan Gu 23 83 0 18 Sep 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 17 33 0 01 May 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
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 281 2,889 0 15 Sep 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 136 1,198 0 16 Aug 2016
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 84 736 0 19 Mar 2014