2024 "convergence rate analysis" Papers
12 papers found
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
ICML 2024posterarXiv:2206.05248
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning
Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee et al.
ICML 2024posterarXiv:2310.11897
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov et al.
ICML 2024posterarXiv:2403.03852
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
ICML 2024poster
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
Yilong Wang, Haishan Ye, Guang Dai et al.
ICML 2024poster
Double Momentum Method for Lower-Level Constrained Bilevel Optimization
Wanli Shi, Yi Chang, Bin Gu
ICML 2024posterarXiv:2406.17386
Enabling Uncertainty Estimation in Iterative Neural Networks
Nikita Durasov, Doruk Oner, Jonathan Donier et al.
ICML 2024posterarXiv:2403.16732
Federated Representation Learning in the Under-Parameterized Regime
Renpu Liu, Cong Shen, Jing Yang
ICML 2024posterarXiv:2406.04596
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang et al.
ICML 2024posterarXiv:2106.08414
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Konstantin Mishchenko, Aaron Defazio
ICML 2024posterarXiv:2306.06101
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
ICML 2024posterarXiv:2401.13971
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
ICML 2024posterarXiv:2406.01870