DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics

20 November 2022

Weizhong Zhang

Jiahui Gao

Papers citing "DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics"

43 / 43 papers shown

Title
Robust Federated Learning against both Data Heterogeneity and Poisoning Attack via Aggregation Optimization Yueqi Xie Weizhong Zhang Renjie Pi Fangzhao Wu Qifeng Chen Xing Xie Sunghun Kim FedML 77 7 0 10 Nov 2022
Privacy for Free: How does Dataset Condensation Help Privacy? Tian Dong Bo Zhao Lingjuan Lyu DD 86 116 0 01 Jun 2022
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning Yae Jee Cho Andre Manoel Gauri Joshi Robert Sim Dimitrios Dimitriadis FedML 87 133 0 27 Apr 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 182 393 0 22 Mar 2022
GradViT: Gradient Inversion of Vision Transformers Ali Hatamizadeh Hongxu Yin H. Roth Wenqi Li Jan Kautz Daguang Xu Pavlo Molchanov ViT 137 64 0 22 Mar 2022
Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning Lin Zhang Li Shen Liang Ding Dacheng Tao Ling-Yu Duan FedML 83 266 0 17 Mar 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 280 30,103 0 01 Mar 2022
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao Song Kai Li Sanjeev Arora FedML AAML SILM 73 275 0 30 Nov 2021
Federated Learning Based on Dynamic Regularization D. A. E. Acar Yue Zhao Ramon Matas Navarro Matthew Mattina P. Whatmough Venkatesh Saligrama FedML 71 781 0 08 Nov 2021
Gradient Inversion with Generative Image Prior Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 65 156 0 28 Oct 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 117 148 0 25 Oct 2021
FedMix: Approximation of Mixup under Mean Augmented Federated Learning Tehrim Yoon Sumin Shin Sung Ju Hwang Eunho Yang FedML 68 171 0 01 Jul 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 80 659 0 20 May 2021
FedFace: Collaborative Learning of Face Recognition Model Divyansh Aggarwal Jiayu Zhou Anil K. Jain FedML 53 61 0 07 Apr 2021
Model-Contrastive Federated Learning Qinbin Li Bingsheng He Basel Alomair FedML 94 1,044 0 30 Mar 2021
Heterogeneity for the Win: One-Shot Federated Clustering D. Dennis Tian Li Virginia Smith FedML 135 151 0 01 Mar 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Yue Liu Yiqun Diao Quan Chen Bingsheng He FedML OOD 151 988 0 03 Feb 2021
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 120 190 0 05 Oct 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 62 262 0 04 Sep 2020
Inverse Distance Aggregation for Federated Learning with Non-IID Data Yousef Yeganeh Azade Farshad Nassir Navab Shadi Albarqouni OOD 52 82 0 17 Aug 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 68 1,337 0 15 Jul 2020
Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup Seungeun Oh Jihong Park Eunjeong Jeong Hyesung Kim M. Bennis Seong-Lyun Kim FedML 77 58 0 17 Jun 2020
Personalized Federated Learning with Moreau Envelopes Canh T. Dinh N. H. Tran Tuan Dung Nguyen FedML 89 1,000 0 16 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 104 1,041 0 12 Jun 2020
Dataset Condensation with Gradient Matching Bo Zhao Konda Reddy Mopuri Hakan Bilen DD 116 501 0 10 Jun 2020
XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning Myungjae Shin Chihoon Hwang Joongheon Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 59 111 0 09 Jun 2020
Federated learning with hierarchical clustering of local updates to improve training on non-IID data Christopher Briggs Zhong Fan Péter András FedML 66 576 0 24 Apr 2020
Survey of Personalization Techniques for Federated Learning V. Kulkarni Milind Kulkarni Aniruddha Pant FedML 230 331 0 19 Mar 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 259 1,777 0 18 Mar 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 259 6,276 0 10 Dec 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 65 347 0 14 Oct 2019
Improving Federated Learning Personalization via Model Agnostic Meta Learning Yihan Jiang Jakub Konecný Keith Rush Sreeram Kannan FedML 75 602 0 27 Sep 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 147 2,343 0 04 Jul 2019
Robust Federated Learning in a Heterogeneous Environment Avishek Ghosh Justin Hong Dong Yin Kannan Ramchandran OOD FedML 61 217 0 16 Jun 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 2,670 0 04 Feb 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 180 5,208 0 14 Dec 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 269 3,213 0 20 Jun 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 165 2,575 0 02 Jun 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 121 1,513 0 05 Mar 2018
Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs Bin Hu Peter M. Seiler Laurent Lessard 102 40 0 03 Nov 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 283 8,904 0 25 Aug 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,260 0 22 Dec 2014