Optimal Algorithms for Stochastic Multi-Level Compositional Optimization

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization

15 February 2022

Papers citing "Optimal Algorithms for Stochastic Multi-Level Compositional Optimization"

15 / 15 papers shown

Title
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization Wei Jiang Sifan Yang Wenhao Yang Yibo Wang Yuanyu Wan Lijun Zhang 28 2 0 06 Jun 2024
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions Wei Jiang Sifan Yang Yibo Wang Lijun Zhang 20 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
Faster Stochastic Variance Reduction Methods for Compositional MiniMax Optimization Jin Liu Xiaokang Pan Junwen Duan Hongdong Li Youqi Li Zhe Qu 22 1 0 18 Aug 2023
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms Minghao Yang Xiyuan Wei Tianbao Yang Yiming Ying 27 1 0 07 Jul 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
Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate Hongchang Gao 11 0 0 06 Jun 2023
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization Feihu Huang FedML 10 1 0 03 Nov 2022
Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization Wei Jiang Gang Li Yibo Wang Lijun Zhang Tianbao Yang 22 16 0 18 Jul 2022
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences Han Shen Tianyi Chen 22 15 0 21 Jun 2022
Algorithmic Foundations of Empirical X-risk Minimization Tianbao Yang 18 5 0 01 Jun 2022
On Tilted Losses in Machine Learning: Theory and Applications Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith 47 38 0 13 Sep 2021
Solving Stochastic Compositional Optimization is Nearly as Easy as Solving Stochastic Optimization Tianyi Chen Yuejiao Sun W. Yin 44 81 0 25 Aug 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 237 11,568 0 09 Mar 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,190 0 16 Aug 2016