FedHB: Hierarchical Bayesian Federated Learning

8 May 2023

Papers citing "FedHB: Hierarchical Bayesian Federated Learning"

10 / 10 papers shown

Title
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard Turner FedML 39 12 0 24 Feb 2022
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric Xing Afshin Rostamizadeh FedML 93 110 0 11 Oct 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 54 260 0 04 Sep 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 49 1,331 0 15 Jul 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 131 574 0 25 Feb 2020
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 65 38 0 09 Aug 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 73 715 0 22 Jul 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 82 806 0 07 Feb 2019
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 1.1K 20,813 0 17 Apr 2017
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 234 4,778 0 04 Jan 2016