ICML 2024 "convergence analysis" Papers
17 papers found
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen et al.
ICML 2024poster
A Persuasive Approach to Combating Misinformation
Safwan Hossain, Andjela Mladenovic, Yiling Chen et al.
ICML 2024posterarXiv:2310.12065
Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions
Yujing Liu, Zhixin Liu, Lei Guo
ICML 2024poster
Convergence of Some Convex Message Passing Algorithms to a Fixed Point
Václav Voráček, Tomáš Werner
ICML 2024spotlight
Delving into the Convergence of Generalized Smooth Minimax Optimization
Wenhan Xian, Ziyi Chen, Heng Huang
ICML 2024poster
Demystifying SGD with Doubly Stochastic Gradients
Kyurae Kim, Joohwan Ko, Yian Ma et al.
ICML 2024poster
Distributed Bilevel Optimization with Communication Compression
Yutong He, Jie Hu, Xinmeng Huang et al.
ICML 2024poster
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang, Shiqiang Wang, Songtao Lu et al.
ICML 2024poster
Faster Adaptive Decentralized Learning Algorithms
Feihu Huang, jianyu zhao
ICML 2024spotlight
Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
Daniil Vankov, Angelia Nedich, Lalitha Sankar
ICML 2024poster
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
Ziqin Chen, Yongqiang Wang
ICML 2024poster
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
Kaan Ozkara, Can Karakus, Parameswaran Raman et al.
ICML 2024poster
On Convergence of Incremental Gradient for Non-convex Smooth Functions
Anastasiia Koloskova, Nikita Doikov, Sebastian Stich et al.
ICML 2024poster
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Fernando, Miao Liu et al.
ICML 2024poster
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier et al.
ICML 2024poster
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian Stich, Martin Jaggi
ICML 2024poster
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook et al.
ICML 2024poster