subMFL: Compatiple subModel Generation for Federated Learning in Device Heterogenous Environment

30 May 2024

Papers citing "subMFL: Compatiple subModel Generation for Federated Learning in Device Heterogenous Environment"

7 / 7 papers shown

Title
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning Hanhan Zhou Tian-Shing Lan Guru Venkataramani Wenbo Ding FedML 42 7 0 27 Jan 2022
AdaptCL: Efficient Collaborative Learning with Dynamic and Adaptive Pruning Guangmeng Zhou Ke Xu Qi Li Yang Liu Yi Zhao 34 8 0 27 Jun 2021
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 68 795 0 28 Jul 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 302 42,038 0 03 Dec 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 56 454 0 26 Sep 2019
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 196 8,807 0 25 Aug 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 246 17,328 0 17 Feb 2016