Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges

14 April 2021

Papers citing "Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges"

6 / 6 papers shown

Title
Federated learning and next generation wireless communications: A survey on bidirectional relationship Debaditya Shome Omer Waqar Wali Ullah Khan 46 31 0 14 Oct 2021
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges Mingzhe Chen Deniz Gündüz Kaibin Huang Walid Saad M. Bennis Aneta Vulgarakis Feljan H. Vincent Poor 45 402 0 05 Apr 2021
Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks Jie Xu Heqiang Wang Lixing Chen FedML 58 43 0 10 Jan 2021
Federated Learning over Noisy Channels: Convergence Analysis and Design Examples Xizixiang Wei Cong Shen FedML 41 15 0 06 Jan 2021
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 1,688 0 14 Apr 2018
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,613 0 17 Apr 2017