ICML 2024 "distributed optimization" Papers
12 papers found
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen et al.
ICML 2024poster
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
Nadav Hallak, Kfir Levy
ICML 2024poster
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
Mengmeng Ma, Tang Li, Xi Peng
ICML 2024poster
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui et al.
ICML 2024poster
Distributed Bilevel Optimization with Communication Compression
Yutong He, Jie Hu, Xinmeng Huang et al.
ICML 2024poster
Faster Adaptive Decentralized Learning Algorithms
Feihu Huang, jianyu zhao
ICML 2024spotlight
Federated Optimization with Doubly Regularized Drift Correction
Xiaowen Jiang, Anton Rodomanov, Sebastian Stich
ICML 2024poster
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova et al.
ICML 2024poster
LASER: Linear Compression in Wireless Distributed Optimization
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels et al.
ICML 2024poster
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
Milad Sefidgaran, Romain Chor, Abdellatif Zaidi et al.
ICML 2024poster
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
Yunyan Bai, Yuxing Liu, Luo Luo
ICML 2024spotlight
Reweighted Solutions for Weighted Low Rank Approximation
David Woodruff, Taisuke Yasuda
ICML 2024poster