A Comprehensive Review on Understanding the Decentralized and Collaborative Approach in Machine Learning

12 March 2025

Papers citing "A Comprehensive Review on Understanding the Decentralized and Collaborative Approach in Machine Learning"

8 / 8 papers shown

Title
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation D. Powers 175 5,288 0 11 Oct 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 259 6,276 0 10 Dec 2019
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks Mingzhe Chen Zhaohui Yang Walid Saad Changchuan Yin H. Vincent Poor Shuguang Cui FedML 76 1,191 0 17 Sep 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges Solmaz Niknam Harpreet S. Dhillon J. H. Reed 60 606 0 30 Jul 2019
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 120 1,404 0 24 Feb 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 309 4,649 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,155 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016