Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space

1 April 2021

Papers citing "Decentralized and Model-Free Federated Learning: Consensus-Based Distillation in Function Space"

7 / 7 papers shown

Title
Soft-Label Caching and Sharpening for Communication-Efficient Federated Distillation Kitsuya Azuma Takayuki Nishio Yuichi Kitagawa Wakako Nakano Takahito Tanimura FedML 72 0 0 28 Apr 2025
Federated Learning with Label-Masking Distillation Jianghu Lu Shikun Li Kexin Bao Pengju Wang Zhenxing Qian Shiming Ge FedML 47 10 0 20 Sep 2024
Multiple Access in the Era of Distributed Computing and Edge Intelligence Nikos G. Evgenidis Nikos A. Mitsiou Vasiliki I. Koutsioumpa Sotiris A. Tegos P. Diamantoulakis G. Karagiannidis 41 8 0 26 Feb 2024
Faster Convergence with Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning over Wireless Networks Daniel Pérez Herrera Zheng Chen Erik G. Larsson 26 1 0 24 Jan 2024
Knowledge Distillation in Federated Edge Learning: A Survey Zhiyuan Wu Sheng Sun Yuwei Wang Min Liu Xue Jiang Runhan Li Bo Gao FedML 35 4 0 14 Jan 2023
The Effect of Training Parameters and Mechanisms on Decentralized Federated Learning based on MNIST Dataset Zhuofan Zhang Mi Zhou K. Niu C. Abdallah FedML 44 1 0 07 Aug 2021
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 278 404 0 09 Apr 2018