FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

4 September 2020

Wei-Lun Chao

Papers citing "FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning"

5 / 55 papers shown

Title
FedADC: Accelerated Federated Learning with Drift Control Emre Ozfatura Kerem Ozfatura Deniz Gunduz FedML 43 37 0 16 Dec 2020
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 25 45 0 11 Sep 2020
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models Zhengming Zhang Yaoqing Yang Z. Yao Yujun Yan Joseph E. Gonzalez Michael W. Mahoney FedML 39 36 0 26 Aug 2020
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 174 763 0 28 Sep 2019
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