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Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016

Dave Bacon

Papers citing "Federated Learning: Strategies for Improving Communication Efficiency"

50 / 1,869 papers shown

Title
LoMar: A Local Defense Against Poisoning Attack on Federated Learning Xingyu Li Zhe Qu Shangqing Zhao Bo Tang Zhuo Lu Yao-Hong Liu AAML 112 97 0 08 Jan 2022
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction Haizhou Liu Xuan Zhang Xinwei Shen Hongbin Sun FedML 82 6 0 08 Jan 2022
BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing Yoshitomo Matsubara Davide Callegaro Sameer Singh Marco Levorato Francesco Restuccia 78 41 0 07 Jan 2022
Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory Nicole Mitchell Johannes Ballé Zachary B. Charles Jakub Konecný FedML 146 21 0 07 Jan 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients Jaemin Shin Yuanchun Li Yunxin Liu Sung-Ju Lee FedML 76 77 0 05 Jan 2022
Integrating Human-in-the-loop into Swarm Learning for Decentralized Fake News Detection Xishuang Dong Lijun Qian 94 9 0 04 Jan 2022
Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers Nikola Popovic D. Paudel Thomas Probst Luc Van Gool 90 1 0 30 Dec 2021
Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning Junyu Shi Wei Wan Shengshan Hu Jianrong Lu L. Zhang AAML 110 86 0 29 Dec 2021
Robust Convergence in Federated Learning through Label-wise Clustering Hunmin Lee Yueyang Liu Donghyun Kim Yingshu Li FedML 74 2 0 28 Dec 2021
Resource-Efficient and Delay-Aware Federated Learning Design under Edge Heterogeneity David Nickel F. Lin Seyyedali Hosseinalipour Nicolò Michelusi Christopher G. Brinton FedML 83 1 0 27 Dec 2021
FRuDA: Framework for Distributed Adversarial Domain Adaptation Shaoduo Gan Akhil Mathur Anton Isopoussu F. Kawsar N. Bianchi-Berthouze Nicholas D. Lane 70 13 0 26 Dec 2021
Faster Rates for Compressed Federated Learning with Client-Variance Reduction Haoyu Zhao Konstantin Burlachenko Zhize Li Peter Richtárik FedML 126 13 0 24 Dec 2021
EIFFeL: Ensuring Integrity for Federated Learning A. Chowdhury Chuan Guo S. Jha Laurens van der Maaten FedML 140 78 0 23 Dec 2021
FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition Chih-Ting Liu Chien-Yi Wang Shao-Yi Chien S. Lai FedML 95 37 0 23 Dec 2021
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation Xingyu Li Zhe Qu Bo Tang Zhuo Lu FedML 109 29 0 22 Dec 2021
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling Bing Luo Wenli Xiao Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 120 179 0 21 Dec 2021
Distributed Machine Learning and the Semblance of Trust Dmitrii Usynin Alexander Ziller Daniel Rueckert Jonathan Passerat-Palmbach Georgios Kaissis 46 1 0 21 Dec 2021
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better Sameer Bibikar H. Vikalo Zhangyang Wang Xiaohan Chen FedML 93 106 0 18 Dec 2021
A Review on Visual Privacy Preservation Techniques for Active and Assisted Living Siddharth Ravi Pau Climent-Pérez Francisco Flórez-Revuelta 88 35 0 17 Dec 2021
CodedPaddedFL and CodedSecAgg: Straggler Mitigation and Secure Aggregation in Federated Learning Reent Schlegel Siddhartha Kumar E. Rosnes Alexandre Graell i Amat FedML 81 45 0 16 Dec 2021
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning Yi Zhou Parikshit Ram Theodoros Salonidis Nathalie Baracaldo Horst Samulowitz Heiko Ludwig AI4CE 86 25 0 15 Dec 2021
Analysis and Evaluation of Synchronous and Asynchronous FLchain F. Wilhelmi L. Giupponi Paolo Dini 78 7 0 15 Dec 2021
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization Huiming Chen Huandong Wang Quanming Yao Yong Li Depeng Jin Qiang Yang FedML 77 6 0 15 Dec 2021
Optimal Rate Adaption in Federated Learning with Compressed Communications Laizhong Cui Xiaoxin Su Yipeng Zhou Jiangchuan Liu FedML 102 43 0 13 Dec 2021
Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image Augmentation Alper Cetinkaya M. Akin Ş. Sağiroğlu OOD FedML 56 18 0 12 Dec 2021
Federated Reinforcement Learning at the Edge Konstantinos Gatsis FedML 73 5 0 11 Dec 2021
Federated Two-stage Learning with Sign-based Voting Zichen Ma Zihan Lu Yu Lu Wenye Li Jinfeng Yi Shuguang Cui FedML 59 2 0 10 Dec 2021
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records Tianyi Zhang Shirui Zhang Ziwei Chen Dianbo Liu FedML 93 4 0 10 Dec 2021
Specificity-Preserving Federated Learning for MR Image Reconstruction Chun-Mei Feng Yu-bao Yan Shanshan Wang Yong Xu Ling Shao Huazhu Fu OOD 133 80 0 09 Dec 2021
FastSGD: A Fast Compressed SGD Framework for Distributed Machine Learning Keyu Yang Lu Chen Zhihao Zeng Yunjun Gao 64 9 0 08 Dec 2021
Locally Differentially Private Sparse Vector Aggregation Mingxun Zhou Tianhao Wang T-H. Hubert Chan Giulia Fanti E. Shi FedML 137 29 0 07 Dec 2021
Intrinisic Gradient Compression for Federated Learning Luke Melas-Kyriazi Franklyn Wang FedML 30 3 0 05 Dec 2021
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning Ayush Chopra Surya Kant Sahu Abhishek Singh Abhinav Java Praneeth Vepakomma Vivek Sharma Ramesh Raskar 96 27 0 02 Dec 2021
Mixing Deep Learning and Multiple Criteria Optimization: An Application to Distributed Learning with Multiple Datasets D. Torre D. Liuzzi M. Repetto M. Rocca 63 1 0 02 Dec 2021
Context-Aware Online Client Selection for Hierarchical Federated Learning Zhe Qu Rui Duan Lixing Chen Jie Xu Zhuo Lu Yao-Hong Liu 94 64 0 02 Dec 2021
Communication-Efficient Federated Learning via Quantized Compressed Sensing Yong-Nam Oh Namyoon Lee Yo-Seb Jeon H. Vincent Poor FedML MQ 80 37 0 30 Nov 2021
Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression François Gauthier Vinay Chakravarthi Gogineni Stefan Werner Yih-Fang Huang A. Kuh FedML 68 9 0 27 Nov 2021
Federated Deep Learning in Electricity Forecasting: An MCDM Approach M. Repetto D. Torre M. Tariq 43 2 0 27 Nov 2021
Dynamic Network-Assisted D2D-Aided Coded Distributed Learning Nikita Zeulin O. Galinina N. Himayat Sergey D. Andreev R. Heath 80 5 0 26 Nov 2021
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning Elnur Gasanov Ahmed Khaled Samuel Horváth Peter Richtárik FedML 98 16 0 22 Nov 2021
Federated Social Recommendation with Graph Neural Network Zhiwei Liu Liangwei Yang Ziwei Fan Hao Peng Philip S. Yu FedML 97 157 0 21 Nov 2021
Satellite Based Computing Networks with Federated Learning Hao Chen Ming Xiao Zhibo Pang 53 86 0 20 Nov 2021
Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective Xuezhen Tu Kun Zhu Nguyen Cong Luong Dusit Niyato Yang Zhang Juan Li FedML AI4CE 97 124 0 20 Nov 2021
Over-the-Air Federated Learning with Retransmissions (Extended Version) Henrik Hellström Viktoria Fodor Carlo Fischione 63 2 0 19 Nov 2021
Client Selection in Federated Learning based on Gradients Importance Ouiame Marnissi Hajar Elhammouti El Houcine Bergou FedML 56 18 0 19 Nov 2021
Training Neural Networks with Fixed Sparse Masks Yi-Lin Sung Varun Nair Colin Raffel FedML 111 209 0 18 Nov 2021
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence Xiang Bai Hanchen Wang Liya Ma Yongchao Xu Jiefeng Gan ... C. Zheng Jianming Wang Zhen Li Carola-Bibiane Schönlieb Tian Xia FedML 84 65 0 18 Nov 2021
Personalized Federated Learning through Local Memorization Othmane Marfoq Giovanni Neglia Laetitia Kameni Richard Vidal FedML 130 95 0 17 Nov 2021
FedCostWAvg: A new averaging for better Federated Learning Leon Mächler Ivan Ezhov Florian Kofler Suprosanna Shit Johannes C. Paetzold T. Loehr Benedikt Wiestler Bjoern Menze FedML OOD 77 13 0 16 Nov 2021
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks M. Ramezani Weilin Cong Mehrdad Mahdavi M. Kandemir A. Sivasubramaniam GNN 100 32 0 16 Nov 2021