Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

13 September 2019

Papers citing "Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification"

50 / 613 papers shown

Title
On-Demand Unlabeled Personalized Federated Learning Ohad Amosy G. Eyal Gal Chechik FedML 46 2 0 16 Nov 2021
DP-REC: Private & Communication-Efficient Federated Learning Aleksei Triastcyn M. Reisser Christos Louizos FedML 26 16 0 09 Nov 2021
Federated Learning Based on Dynamic Regularization D. A. E. Acar Yue Zhao Ramon Matas Navarro Matthew Mattina P. Whatmough Venkatesh Saligrama FedML 27 750 0 08 Nov 2021
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective Margalit Glasgow Honglin Yuan Tengyu Ma FedML 27 43 0 05 Nov 2021
Federated Learning with Heterogeneous Differential Privacy Nasser Aldaghri Hessam Mahdavifar Ahmad Beirami FedML 35 2 0 28 Oct 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 43 71 0 27 Oct 2021
Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design Zhe Zhang Shiyao Ma Jiangtian Nie Yi Wu Qiang Yan Xiaoke Xu Dusit Niyato FedML 21 16 0 26 Oct 2021
FedGEMS: Federated Learning of Larger Server Models via Selective Knowledge Fusion Sijie Cheng Jingwen Wu Yanghua Xiao Yang Liu Yang Liu FedML 18 67 0 21 Oct 2021
FRL: Federated Rank Learning Hamid Mozaffari Virat Shejwalkar Amir Houmansadr FedML 29 11 0 08 Oct 2021
Neural Tangent Kernel Empowered Federated Learning Kai Yue Richeng Jin Ryan Pilgrim Chau-Wai Wong D. Baron H. Dai FedML 22 17 0 07 Oct 2021
Federated Learning via Plurality Vote Kai Yue Richeng Jin Chau-Wai Wong H. Dai FedML 26 8 0 06 Oct 2021
Efficient and Private Federated Learning with Partially Trainable Networks Hakim Sidahmed Zheng Xu Ankush Garg Yuan Cao Mingqing Chen FedML 54 13 0 06 Oct 2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision Chaoyang He Zhengyu Yang Erum Mushtaq Sunwoo Lee Mahdi Soltanolkotabi A. Avestimehr FedML 98 36 0 06 Oct 2021
FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin Shen Yan Chaoyang He Emilio Ferrara A. Avestimehr FedML 33 197 0 02 Oct 2021
FedProc: Prototypical Contrastive Federated Learning on Non-IID data Xutong Mu Yulong Shen Ke Cheng Xueli Geng Jiaxuan Fu Tao Zhang Zhiwei Zhang FedML 45 162 0 25 Sep 2021
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer Yae Jee Cho Jianyu Wang Tarun Chiruvolu Gauri Joshi FedML 37 31 0 16 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 24 18 0 16 Sep 2021
Iterated Vector Fields and Conservatism, with Applications to Federated Learning Zachary B. Charles Keith Rush 27 6 0 08 Sep 2021
Multi-Center Federated Learning: Clients Clustering for Better Personalization Guodong Long Ming Xie Tao Shen Dinesh Manocha Xianzhi Wang Jing Jiang Chengqi Zhang FedML 32 243 0 19 Aug 2021
Towards More Efficient Federated Learning with Better Optimization Objects Zirui Zhu Ziyi Ye FedML 21 0 0 19 Aug 2021
Federated Multi-Target Domain Adaptation Chun-Han Yao Boqing Gong Huayu Chen Qi Yukun Zhu Ming-Hsuan Yang OOD FedML 11 63 0 17 Aug 2021
Aggregation Delayed Federated Learning Ye Xue Diego Klabjan Yuan Luo FedML OOD 28 5 0 17 Aug 2021
Communication-Efficient Federated Learning via Predictive Coding Kai Yue Richeng Jin Chau-Wai Wong H. Dai FedML 25 14 0 02 Aug 2021
New Metrics to Evaluate the Performance and Fairness of Personalized Federated Learning Siddharth Divi Yi-Shan Lin Habiba Farrukh Z. Berkay Celik FedML 25 17 0 28 Jul 2021
A General Theory for Client Sampling in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 17 13 0 26 Jul 2021
Precision-Weighted Federated Learning Jonatan Reyes Di-Jorio Lisa Cécile Low-Kam Marta Kersten-Oertel FedML 18 36 0 20 Jul 2021
RingFed: Reducing Communication Costs in Federated Learning on Non-IID Data Guang Yang Ke Mu Chunhe Song Zhijia Yang Tierui Gong FedML 24 16 0 19 Jul 2021
An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging Liangqiong Qu N. Balachandar D. Rubin 34 24 0 18 Jul 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 187 412 0 14 Jul 2021
Federated Mixture of Experts M. Reisser Christos Louizos E. Gavves Max Welling FedML 28 25 0 14 Jul 2021
IFedAvg: Interpretable Data-Interoperability for Federated Learning David Roschewitz Mary-Anne Hartley Luca Corinzia Martin Jaggi FedML 22 7 0 14 Jul 2021
Personalized Federated Learning over non-IID Data for Indoor Localization Peng Wu Tales Imbiriba Junha Park Sunwoo Kim Pau Closas FedML 25 28 0 09 Jul 2021
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging Miao Zhang Liangqiong Qu Praveer Singh Jayashree Kalpathy-Cramer D. Rubin OOD FedML 29 62 0 06 Jul 2021
On Bridging Generic and Personalized Federated Learning for Image Classification Hong-You Chen Wei-Lun Chao FedML 29 21 0 02 Jul 2021
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data Dezhong Yao Wanning Pan Yutong Dai Yao Wan Xiaofeng Ding Hai Jin Zheng Xu Lichao Sun FedML 28 50 0 30 Jun 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 32 99 0 29 Jun 2021
Implicit Gradient Alignment in Distributed and Federated Learning Yatin Dandi Luis Barba Martin Jaggi FedML 26 31 0 25 Jun 2021
Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging Liangqiong Qu N. Balachandar Miao Zhang D. Rubin MedIm 22 19 0 24 Jun 2021
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning Hua Huang Fanhua Shang Yuanyuan Liu Hongying Liu FedML 29 14 0 23 Jun 2021
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning Kamil Deja Pawel Wawrzyñski Wojciech Masarczyk Daniel Marczak Tomasz Trzciñski CLL 24 4 0 23 Jun 2021
Compositional federated learning: Applications in distributionally robust averaging and meta learning Feihu Huang Junyi Li FedML 22 15 0 21 Jun 2021
FedCM: Federated Learning with Client-level Momentum Jing Xu Sen Wang Liwei Wang Andrew Chi-Chih Yao FedML 32 94 0 21 Jun 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning Madhusanka Manimel Wadu S. Samarakoon M. Bennis 18 51 0 12 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 38 290 0 11 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Liangqiong Qu Yuyin Zhou Paul Pu Liang Yingda Xia Feifei Wang Ehsan Adeli L. Fei-Fei D. Rubin FedML AI4CE 19 176 0 10 Jun 2021
Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners Vaikkunth Mugunthan P. Goyal Lalana Kagal FedML 32 9 0 10 Jun 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data Mi Luo Fei Chen Dapeng Hu Yifan Zhang Jian Liang Jiashi Feng FedML 45 328 0 09 Jun 2021
Fast Federated Learning in the Presence of Arbitrary Device Unavailability Xinran Gu Kaixuan Huang Jingzhao Zhang Longbo Huang FedML 35 96 0 08 Jun 2021
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning Jinhyun So Ramy E. Ali Başak Güler Jiantao Jiao Salman Avestimehr FedML 45 77 0 07 Jun 2021