Achieving Personalized Federated Learning with Sparse Local Models

27 January 2022

Li Shen

Papers citing "Achieving Personalized Federated Learning with Sparse Local Models"

31 / 31 papers shown

Title
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan Samuel Horváth Martin Takáč Karthik Nandakumar FedML 106 0 0 03 Oct 2024
FedCM: Federated Learning with Client-level Momentum Jing Xu Sen Wang Liwei Wang Andrew Chi-Chih Yao FedML 66 103 0 21 Jun 2021
Top-KAST: Top-K Always Sparse Training Siddhant M. Jayakumar Razvan Pascanu Jack W. Rae Simon Osindero Erich Elsen 110 97 0 07 Jun 2021
Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity Saeed Vahidian Mahdi Morafah Bill Lin 84 59 0 02 May 2021
Exploiting Shared Representations for Personalized Federated Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML OOD 99 712 0 14 Feb 2021
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets Ang Li Jingwei Sun Binghui Wang Lin Duan Sicheng Li Yiran Chen H. Li FedML 64 127 0 07 Aug 2020
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 221 575 0 27 Jul 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 293 553 0 30 Mar 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 144 1,431 0 29 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 131 574 0 25 Feb 2020
Federated Learning of a Mixture of Global and Local Models Filip Hanzely Peter Richtárik FedML 48 381 0 10 Feb 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 108 559 0 06 Jan 2020
Federated Learning with Personalization Layers Manoj Ghuhan Arivazhagan V. Aggarwal Aaditya Kumar Singh Sunav Choudhary FedML 84 830 0 02 Dec 2019
Rigging the Lottery: Making All Tickets Winners Utku Evci Trevor Gale Jacob Menick Pablo Samuel Castro Erich Elsen 162 600 0 25 Nov 2019
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 88 851 0 08 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 135 566 0 01 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 135 1,143 0 13 Sep 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 73 715 0 22 Jul 2019
Sparse Networks from Scratch: Faster Training without Losing Performance Tim Dettmers Luke Zettlemoyer 114 339 0 10 Jul 2019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization Hesham Mostafa Xin Wang 69 311 0 15 Feb 2019
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware Shiwei Liu Decebal Constantin Mocanu A. R. Ramapuram Matavalam Yulong Pei Mykola Pechenizkiy BDL 35 92 0 26 Jan 2019
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 164 1,061 0 24 May 2018
Group Normalization Yuxin Wu Kaiming He 192 3,644 0 22 Mar 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 200 3,457 0 09 Mar 2018
Deep Rewiring: Training very sparse deep networks G. Bellec David Kappel Wolfgang Maass Robert Legenstein BDL 123 277 0 14 Nov 2017
Scalable Training of Artificial Neural Networks with Adaptive Sparse Connectivity inspired by Network Science Decebal Constantin Mocanu Elena Mocanu Peter Stone Phuong H. Nguyen M. Gibescu A. Liotta 148 626 0 15 Jul 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 286 4,636 0 18 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 375 17,399 0 17 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.9K 193,426 0 10 Dec 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 413 43,234 0 11 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.3K 100,213 0 04 Sep 2014