A Stochastic Composite Gradient Method with Incremental Variance Reduction

24 June 2019

Papers citing "A Stochastic Composite Gradient Method with Incremental Variance Reduction"

23 / 23 papers shown

Title
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning Prashant Khanduri Chengyin Li Rafi Ibn Sultan Yao Qiang Joerg Kliewer Dongxiao Zhu 87 0 0 21 Nov 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 84 6 0 02 Jan 2023
Stochastic Constrained DRO with a Complexity Independent of Sample Size Q. Qi Jiameng Lyu Kung-Sik Chan E. Bai Tianbao Yang 109 16 0 11 Oct 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization Wei Jiang Gang Li Yibo Wang Lijun Zhang Tianbao Yang 124 18 0 18 Jul 2022
Algorithmic Foundations of Empirical X-risk Minimization Tianbao Yang 145 6 0 01 Jun 2022
Learning Distributionally Robust Models at Scale via Composite Optimization Farzin Haddadpour Mohammad Mahdi Kamani M. Mahdavi Amin Karbasi OOD 69 5 0 17 Mar 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization Wei Jiang Bokun Wang Yibo Wang Lijun Zhang Tianbao Yang 162 18 0 15 Feb 2022
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization Guanghui Wang Minghao Yang Lijun Zhang Tianbao Yang 83 22 0 02 Jul 2021
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems Tianyi Chen Yuejiao Sun W. Yin 80 33 0 25 Jun 2021
Randomized Stochastic Variance-Reduced Methods for Multi-Task Stochastic Bilevel Optimization Zhishuai Guo Quan Hu Lijun Zhang Tianbao Yang 142 31 0 05 May 2021
Finite-Time Convergence Rates of Nonlinear Two-Time-Scale Stochastic Approximation under Markovian Noise Thinh T. Doan 94 16 0 04 Apr 2021
On the Importance of Sampling in Training GCNs: Tighter Analysis and Variance Reduction Weilin Cong M. Ramezani M. Mahdavi 62 5 0 03 Mar 2021
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method Junyu Zhang Chengzhuo Ni Zheng Yu Csaba Szepesvári Mengdi Wang 125 69 0 17 Feb 2021
A Single-Timescale Method for Stochastic Bilevel Optimization Tianyi Chen Yuejiao Sun Quan-Wu Xiao W. Yin 93 79 0 09 Feb 2021
Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance Thinh T. Doan 92 46 0 03 Nov 2020
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization Tianyi Chen Yuejiao Sun W. Yin 139 82 0 25 Aug 2020
Hybrid Variance-Reduced SGD Algorithms For Nonconvex-Concave Minimax Problems Quoc Tran-Dinh Deyi Liu Lam M. Nguyen 80 13 0 27 Jun 2020
An Online Method for A Class of Distributionally Robust Optimization with Non-Convex Objectives Qi Qi Zhishuai Guo Yi Tian Xu Rong Jin Tianbao Yang 102 47 0 17 Jun 2020
Momentum-based variance-reduced proximal stochastic gradient method for composite nonconvex stochastic optimization Yangyang Xu Yibo Xu 69 25 0 31 May 2020
Momentum with Variance Reduction for Nonconvex Composition Optimization Ziyi Chen Yi Zhou ODL 64 3 0 15 May 2020
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization Quoc Tran-Dinh Nhan H. Pham Lam M. Nguyen 64 24 0 17 Feb 2020
Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic Approximation Thinh T. Doan 82 36 0 23 Dec 2019
Multi-Level Composite Stochastic Optimization via Nested Variance Reduction Junyu Zhang Lin Xiao 132 56 0 29 Aug 2019