FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

26 February 2021

Papers citing "FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout"

7 / 157 papers shown

Title
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 411 0 14 Jul 2021
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions Stefanos Laskaridis Alexandros Kouris Nicholas D. Lane TPM 18 107 0 09 Jun 2021
Asynchronous speedup in decentralized optimization Mathieu Even Hadrien Hendrikx Laurent Massoulie 18 4 0 07 Jun 2021
End-to-End Speech Recognition from Federated Acoustic Models Yan Gao Titouan Parcollet Salah Zaiem Javier Fernandez-Marques Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane 25 43 0 29 Apr 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 787 0 15 Feb 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 1,687 0 14 Apr 2018
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,329 0 05 Nov 2016