Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms

11 October 2020

Papers citing "Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms"

23 / 23 papers shown

Title
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble Jacopo Talpini Marco Savi Giovanni Neglia FedML Presented at ResearchTrend Connect \| FedML on 07 May 2025 76 0 0 19 Mar 2025
Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning Yanbiao Ma Wei-Ming Dai Wenke Huang Jiayi Chen 94 0 0 09 Mar 2025
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan Samuel Horváth Martin Takáč Karthik Nandakumar FedML 57 0 0 03 Oct 2024
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers Alexandros E. Tzikas Licio Romao Mert Pilanci Alessandro Abate Mykel J. Kochenderfer 26 0 0 29 Jan 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
Distributed Variational Inference for Online Supervised Learning P. Paritosh Nikolay A. Atanasov Sonia Martinez 27 1 0 05 Sep 2023
Personalized Federated Learning via Amortized Bayesian Meta-Learning Shiyu Liu Shaogao Lv Dun Zeng Zenglin Xu Hongya Wang Yue Yu FedML 20 3 0 05 Jul 2023
Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models Yuchao Gu Xintao Wang Jay Zhangjie Wu Yujun Shi Yunpeng Chen ... Shuning Chang Wei Yu Wu Yixiao Ge Ying Shan Mike Zheng Shou DiffM 38 166 0 29 May 2023
Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets Marianne A Jonker H. Pazira Anthony C. C. Coolen FedML 20 5 0 15 Feb 2023
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy Zhifeng Jiang Wei Wang Ruichuan Chen 38 6 0 26 Sep 2022
Federated Learning with Label Distribution Skew via Logits Calibration Jie M. Zhang Zhiqi Li Bo-wen Li Jianghe Xu Shuang Wu Shouhong Ding Chao Wu FedML 10 140 0 01 Sep 2022
Multi-Level Branched Regularization for Federated Learning Jinkyu Kim Geeho Kim Bohyung Han FedML 10 53 0 14 Jul 2022
Personalized Federated Learning via Variational Bayesian Inference Xu Zhang Yinchuan Li Wenpeng Li Kaiyang Guo Yunfeng Shao FedML 36 85 0 16 Jun 2022
FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement Hao Zhang Tingting Wu Siyao Cheng Jie Liu FedML 30 11 0 07 Apr 2022
Adaptive Aggregation For Federated Learning K. R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 19 16 0 23 Mar 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 20 16 0 09 Dec 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 24 71 0 27 Oct 2021
The Skellam Mechanism for Differentially Private Federated Learning Naman Agarwal Peter Kairouz Ziyu Liu FedML 11 121 0 11 Oct 2021
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning Charlie Hou K. K. Thekumparampil Giulia Fanti Sewoong Oh FedML 30 14 0 16 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 173 411 0 14 Jul 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 27 78 0 08 Jun 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 16 232 0 12 Feb 2021
Federated Composite Optimization Honglin Yuan Manzil Zaheer Sashank J. Reddi FedML 24 57 0 17 Nov 2020