Federated Reconstruction: Partially Local Federated Learning

5 February 2021

Papers citing "Federated Reconstruction: Partially Local Federated Learning"

25 / 25 papers shown

Title
Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data Wentai Wu Ligang He Saiqin Long Ahmed M. Abdelmoniem Yingliang Wu Rui Mao 55 0 0 05 Mar 2025
The Effect of Personalization in FedProx: A Fine-grained Analysis on Statistical Accuracy and Communication Efficiency Xin Yu Zelin He Ying Sun Lingzhou Xue Runze Li FedML 26 0 0 11 Oct 2024
Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security Youyang Qu Ming Liu Tianqing Zhu Longxiang Gao Shui Yu Wanlei Zhou MU FedML 54 2 0 14 Jun 2024
PraFFL: A Preference-Aware Scheme in Fair Federated Learning Rongguang Ye Wei-Bin Kou Ming Tang FedML 31 4 0 13 Apr 2024
Personalised Federated Learning On Heterogeneous Feature Spaces A. Rakotomamonjy Maxime Vono H. M. Ruiz L. Ralaivola FedML 18 8 0 26 Jan 2023
Privacy and Efficiency of Communications in Federated Split Learning Zongshun Zhang Andrea Pinto Valeria Turina Flavio Esposito I. Matta FedML 19 32 0 04 Jan 2023
A Survey on Federated Recommendation Systems Zehua Sun Yonghui Xu Y. Liu Weiliang He Lanju Kong Fangzhao Wu Y. Jiang Li-zhen Cui FedML 24 60 0 27 Dec 2022
Learning to Generate Image Embeddings with User-level Differential Privacy Zheng Xu Maxwell D. Collins Yuxiao Wang Liviu Panait Sewoong Oh S. Augenstein Ting Liu Florian Schroff H. B. McMahan FedML 30 29 0 20 Nov 2022
Watermarking in Secure Federated Learning: A Verification Framework Based on Client-Side Backdooring Wenyuan Yang Shuo Shao Yue Yang Xiyao Liu Ximeng Liu Zhihua Xia Gerald Schaefer Hui Fang FedML 12 21 0 14 Nov 2022
Federated Fuzzy Neural Network with Evolutionary Rule Learning Leijie Zhang Ye-ling Shi Yu-Cheng Chang Chin-Teng Lin FedML 19 15 0 26 Oct 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 21 11 0 14 Oct 2022
Generalized Federated Learning via Sharpness Aware Minimization Zhe Qu Xingyu Li Rui Duan Yaojiang Liu Bo Tang Zhuo Lu FedML 20 130 0 06 Jun 2022
Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity Kiwan Maeng Haiyu Lu Luca Melis John Nguyen Michael G. Rabbat Carole-Jean Wu FedML 29 31 0 30 May 2022
Federated Learning with Partial Model Personalization Krishna Pillutla Kshitiz Malik Abdel-rahman Mohamed Michael G. Rabbat Maziar Sanjabi Lin Xiao FedML 39 154 0 08 Apr 2022
Personalized Federated Learning with Exact Stochastic Gradient Descent Sotirios Nikoloutsopoulos I. Koutsopoulos Michalis K. Titsias FedML 23 9 0 20 Feb 2022
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams S. Denisov H. B. McMahan J. Rush Adam D. Smith Abhradeep Thakurta FedML 19 59 0 16 Feb 2022
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning A. Bietti Chen-Yu Wei Miroslav Dudík John Langford Zhiwei Steven Wu FedML 20 43 0 10 Feb 2022
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
Efficient and Private Federated Learning with Partially Trainable Networks Hakim Sidahmed Zheng Xu Ankush Garg Yuan Cao Mingqing Chen FedML 49 13 0 06 Oct 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
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 787 0 15 Feb 2021
FedADC: Accelerated Federated Learning with Drift Control Emre Ozfatura Kerem Ozfatura Deniz Gunduz FedML 27 37 0 16 Dec 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 186 542 0 30 Mar 2020
FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning Suyu Ge Fangzhao Wu Chuhan Wu Tao Qi Yongfeng Huang Xing Xie 158 56 0 20 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 281 11,681 0 09 Mar 2017