Federated Learning in IoT: a Survey from a Resource-Constrained Perspective

25 August 2023

Papers citing "Federated Learning in IoT: a Survey from a Resource-Constrained Perspective"

18 / 18 papers shown

Title
TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training Tuo Zhang Lei Gao Sunwoo Lee Mi Zhang Salman Avestimehr FedML 67 30 0 14 Apr 2023
Generative Data Augmentation for Non-IID Problem in Decentralized Clinical Machine Learning Zirui Wang Shaoming Duan Chengyue Wu Wenhao Lin Xin-Xiang Zha Peiyi Han Chuanyi Liu MedIm 43 4 0 02 Dec 2022
Achieving Personalized Federated Learning with Sparse Local Models Tiansheng Huang Shiwei Liu Li Shen Fengxiang He Weiwei Lin Dacheng Tao FedML 71 44 0 27 Jan 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients Jaemin Shin Yuanchun Li Yunxin Liu Sung-Ju Lee FedML 48 74 0 05 Jan 2022
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models Lan Zhang Dapeng Wu Xiaoyong Yuan FedML 55 48 0 08 Sep 2021
FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers Zheng Chai Yujing Chen Ali Anwar Liang Zhao Yue Cheng Huzefa Rangwala FedML 53 123 0 12 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 96 556 0 03 Oct 2020
An Efficient Framework for Clustered Federated Learning Avishek Ghosh Jichan Chung Dong Yin Kannan Ramchandran FedML 65 858 0 07 Jun 2020
UVeQFed: Universal Vector Quantization for Federated Learning Nir Shlezinger Mingzhe Chen Yonina C. Eldar H. Vincent Poor Shuguang Cui FedML MQ 54 227 0 05 Jun 2020
TRP: Trained Rank Pruning for Efficient Deep Neural Networks Yuhui Xu Yuxi Li Shuai Zhang W. Wen Botao Wang Y. Qi Yiran Chen Weiyao Lin H. Xiong AAML 60 71 0 30 Apr 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 174 1,434 0 29 Feb 2020
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 88 853 0 08 Oct 2019
Client-Edge-Cloud Hierarchical Federated Learning Lumin Liu Jun Zhang S. H. Song Khaled B. Letaief FedML 70 742 0 16 May 2019
Quantizing deep convolutional networks for efficient inference: A whitepaper Raghuraman Krishnamoorthi MQ 129 1,015 0 21 Jun 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 242 1,706 0 14 Apr 2018
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 390 17,453 0 17 Feb 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 253 8,832 0 01 Oct 2015
Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition V. Lebedev Yaroslav Ganin M. Rakhuba Ivan Oseledets Victor Lempitsky 61 884 0 19 Dec 2014