Solving Stochastic Compositional Optimization is Nearly as Easy as
Solving Stochastic Optimization

Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization

25 August 2020

Tianyi Chen

Papers citing "Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization"

11 / 11 papers shown

Title
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning Sihan Zeng Thinh T. Doan 41 5 0 15 May 2024
Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization Nachuan Xiao Kuang-Yu Ding Xiaoyin Hu Kim-Chuan Toh 14 2 0 15 Apr 2024
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning Prashant Khanduri Chengyin Li Rafi Ibn Sultan Yao Qiang Joerg Kliewer Dongxiao Zhu 25 0 0 21 Nov 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 17 2 0 01 Aug 2023
Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization Hongchang Gao 17 1 0 25 Jul 2023
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms Minghao Yang Xiyuan Wei Tianbao Yang Yiming Ying 19 1 0 07 Jul 2023
Fairness via Adversarial Attribute Neighbourhood Robust Learning Q. Qi Shervin Ardeshir Yi Tian Xu Tianbao Yang 27 0 0 12 Oct 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization Wei Jiang Gang Li Yibo Wang Lijun Zhang Tianbao Yang 12 16 0 18 Jul 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization Wei Jiang Bokun Wang Yibo Wang Lijun Zhang Tianbao Yang 59 17 0 15 Feb 2022
Compositional ADAM: An Adaptive Compositional Solver Rasul Tutunov Minne Li Alexander I. Cowen-Rivers Jun Wang Haitham Bou-Ammar ODL 43 16 0 10 Feb 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 234 11,568 0 09 Mar 2017