Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent

11 September 2020

Osvaldo Simeone

Papers citing "Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent"

30 / 30 papers shown

Title
Bayesian Federated Learning for Continual Training Usevalad Milasheuski Luca Barbieri Sanaz Kianoush M. Nicoli S. Savazzi FedML 38 0 0 21 Apr 2025
Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization Shivam Pal Aishwarya Gupta Saqib Sarwar Piyush Rai FedML 85 0 0 27 Nov 2024
A Bayesian Framework for Clustered Federated Learning Peng Wu Tales Imbiriba Pau Closas FedML 51 0 0 20 Oct 2024
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning Boning Zhang Dongzhu Liu Osvaldo Simeone Guanchu Wang Dimitrios Pezaros Guangxu Zhu BDL FedML 33 0 0 18 Oct 2024
Long-time asymptotics of noisy SVGD outside the population limit Victor Priser Pascal Bianchi Adil Salim 40 1 0 17 Jun 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks Hengzhu Liu Ping Xiong Tianqing Zhu Philip S. Yu 27 6 0 10 Jun 2024
Variational Bayes for Federated Continual Learning Dezhong Yao Sanmu Li Yutong Dai Zhiqiang Xu Shengshan Hu Peilin Zhao Lichao Sun FedML 48 1 0 23 May 2024
Compressed Bayesian Federated Learning for Reliable Passive Radio Sensing in Industrial IoT Luca Barbieri S. Savazzi M. Nicoli 25 1 0 09 May 2024
Cooperation and Federation in Distributed Radar Point Cloud Processing S. Savazzi V. Rampa Sanaz Kianoush Alberto Minora L. Costa 32 0 0 03 May 2024
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune Mengen Luo Chi Xu E. Kuruoglu FedML 28 0 0 25 Feb 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 32 3 0 16 Jan 2024
Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics Nicolò Romandini Alessio Mora Carlo Mazzocca R. Montanari Paolo Bellavista FedML MU 56 22 0 10 Jan 2024
Be Bayesian by Attachments to Catch More Uncertainty Shiyu Shen Bin Pan Tianyang Shi Tao Li Zhenwei Shi UQCV 22 0 0 19 Oct 2023
Bayesian Federated Learning: A Survey LongBing Cao Hui Chen Xuhui Fan João Gama Yew-Soon Ong Vipin Kumar FedML 26 21 0 26 Apr 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 23 6 0 08 Mar 2023
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks Jiali Cheng George Dasoulas Huan He Chirag Agarwal Marinka Zitnik MU 24 35 0 26 Feb 2023
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach Han Guo P. Greengard Hongyi Wang Andrew Gelman Yoon Kim Eric P. Xing FedML 21 20 0 08 Feb 2023
Client Selection for Federated Bayesian Learning Jiarong Yang Yuan Liu Rahif Kassab FedML 29 11 0 11 Dec 2022
Improved Stein Variational Gradient Descent with Importance Weights Lukang Sun Peter Richtárik 18 3 0 02 Oct 2022
Compressed Particle-Based Federated Bayesian Learning and Unlearning J. Gong Osvaldo Simeone Joonhyuk Kang FedML 44 10 0 14 Sep 2022
Federated Learning with Uncertainty via Distilled Predictive Distributions Shreyansh P. Bhatt Aishwarya Gupta Piyush Rai FedML 16 10 0 15 Jun 2022
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition Lukang Sun Avetik G. Karagulyan Peter Richtárik 21 19 0 01 Jun 2022
Robust Distributed Bayesian Learning with Stragglers via Consensus Monte Carlo Hari Hara Suthan Chittoor Osvaldo Simeone 13 0 0 17 Dec 2021
Forget-SVGD: Particle-Based Bayesian Federated Unlearning J. Gong Osvaldo Simeone Rahif Kassab Joonhyuk Kang FedML MU 11 23 0 23 Nov 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 21 98 0 29 Jun 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 11 20 0 06 Jun 2021
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning Maxime Vono Vincent Plassier Alain Durmus Aymeric Dieuleveut Eric Moulines FedML 22 35 0 01 Jun 2021
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks J. Gong Osvaldo Simeone Joonhyuk Kang FedML MU 13 12 0 08 Apr 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 21 401 0 05 Apr 2021
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 193 498 0 11 Jun 2018