Federated Learning: Challenges, Methods, and Future Directions

21 August 2019

Papers citing "Federated Learning: Challenges, Methods, and Future Directions"

8 / 558 papers shown

Title
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 43 2,278 0 04 Jul 2019
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art Viet Quoc Pham Fang Fang H. Vu Md. Jalil Piran Mai Le L. Le W. Hwang Z. Ding 23 596 0 20 Jun 2019
Wireless Network Intelligence at the Edge Jihong Park S. Samarakoon M. Bennis Mérouane Debbah 19 518 0 07 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 36 1,390 0 03 Dec 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,687 0 14 Apr 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD Sanghamitra Dutta Gauri Joshi Soumyadip Ghosh Parijat Dube P. Nagpurkar 17 193 0 03 Mar 2018
Federated Meta-Learning with Fast Convergence and Efficient Communication Fei Chen Mi Luo Zhenhua Dong Zhenguo Li Xiuqiang He FedML 34 388 0 22 Feb 2018
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010