Iterated Vector Fields and Conservatism, with Applications to Federated Learning

8 September 2021

Papers citing "Iterated Vector Fields and Conservatism, with Applications to Federated Learning"

7 / 7 papers shown

Title
Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo Zachary B. Charles Gabriel Teston Lucio Dery Keith Rush Nova Fallen Zachary Garrett Arthur Szlam Arthur Douillard 122 0 0 12 Mar 2025
Leveraging Function Space Aggregation for Federated Learning at Scale Nikita Dhawan Nicole Mitchell Zachary B. Charles Zachary Garrett Gintare Karolina Dziugaite FedML 17 3 0 17 Nov 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary B. Charles Nicole Mitchell Krishna Pillutla Michael Reneer Zachary Garrett FedML AI4CE 28 28 0 18 Jul 2023
Federated Automatic Differentiation Keith Rush Zachary B. Charles Zachary Garrett FedML 34 1 0 18 Jan 2023
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data Jianyu Wang Rudrajit Das Gauri Joshi Satyen Kale Zheng Xu Tong Zhang FedML 26 38 0 09 Jun 2022
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 173 411 0 14 Jul 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,198 0 16 Aug 2016