Multi-block-Single-probe Variance Reduced Estimator for Coupled
Compositional Optimization

Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization

18 July 2022

Papers citing "Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization"

16 / 16 papers shown

Title
Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints Ming Yang Gang Li Quanqi Hu Qihang Lin Tianbao Yang 17 0 0 21 Apr 2025
Communication-Efficient Federated Group Distributionally Robust Optimization Zhishuai Guo Tianbao Yang FedML 23 0 0 08 Oct 2024
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization Wei Jiang Sifan Yang Wenhao Yang Yibo Wang Yuanyu Wan Lijun Zhang 26 0 0 06 Jun 2024
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions Wei Jiang Sifan Yang Yibo Wang Lijun Zhang 18 1 0 04 Jun 2024
Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction Wei Jiang Sifan Yang Wenhao Yang Lijun Zhang 13 3 0 01 Jun 2024
Efficient Algorithms for Empirical Group Distributional Robust Optimization and Beyond Dingzhi Yu Yu-yan Cai Wei Jiang Lijun Zhang 33 5 0 06 Mar 2024
Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization Quanqi Hu Dixian Zhu Tianbao Yang 14 8 0 05 Oct 2023
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining Xidong Wu Zhengmian Hu Jian Pei Heng Huang 14 12 0 06 Aug 2023
Learning Unnormalized Statistical Models via Compositional Optimization Wei Jiang Jiayu Qin Lingyu Wu Changyou Chen Tianbao Yang Lijun Zhang 11 3 0 13 Jun 2023
LibAUC: A Deep Learning Library for X-Risk Optimization Zhuoning Yuan Dixian Zhu Zimeng Qiu Gang Li Xuanhui Wang Tianbao Yang BDL 30 8 0 05 Jun 2023
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization Quanqi Hu Zimeng Qiu Zhishuai Guo Lijun Zhang Tianbao Yang 11 4 0 30 May 2023
Debiasing Conditional Stochastic Optimization Lie He S. Kasiviswanathan CML BDL 25 4 0 20 Apr 2023
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Zhishuai Guo R. L. Jin Jiebo Luo Tianbao Yang FedML 27 7 0 26 Oct 2022
Algorithmic Foundations of Empirical X-risk Minimization Tianbao Yang 18 5 0 01 Jun 2022
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization Tianyi Chen Yuejiao Sun W. Yin 44 81 0 25 Aug 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 114 1,190 0 16 Aug 2016