Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach

8 February 2023

Papers citing "Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach"

24 / 24 papers shown

Title
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan Samuel Horváth Martin Takáč Karthik Nandakumar FedML 125 0 0 03 Oct 2024
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 54 12 0 24 Feb 2022
FedJAX: Federated learning simulation with JAX Jae Hun Ro A. Suresh Ke Wu FedML 90 49 0 04 Aug 2021
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 273 419 0 14 Jul 2021
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric Xing Afshin Rostamizadeh FedML 101 112 0 11 Oct 2020
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 78 46 0 11 Sep 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 231 577 0 27 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 66 1,337 0 15 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods Zachary B. Charles Jakub Konecný FedML 78 54 0 02 Jul 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 177 1,437 0 29 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 256 6,261 0 10 Dec 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 75 572 0 18 Nov 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 136 247 0 06 Jun 2019
Limitations of the Empirical Fisher Approximation for Natural Gradient Descent Frederik Kunstner Lukas Balles Philipp Hennig 77 217 0 29 May 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 84 808 0 07 Feb 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 121 2,666 0 04 Feb 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 129 935 0 01 Feb 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 149 272 0 13 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 178 691 0 15 Nov 2017
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 55 597 0 13 Apr 2017
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 138 1,899 0 08 Oct 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 246 886 0 06 Nov 2015
Stochastic Expectation Propagation Yingzhen Li Jose Miguel Hernandez-Lobato Richard Turner 133 115 0 12 Jun 2015
Expectation Propagation for approximate Bayesian inference T. Minka 132 1,907 0 10 Jan 2013