ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity

4 August 2022

Xinchi Qiu

Javier Fernandez-Marques

Papers citing "ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity"

45 / 45 papers shown

Title
PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning Yisu Wang Ruilong Wu Xinjiao Li Dirk Kutscher 235 0 0 24 May 2025
Communication Efficiency in Federated Learning: Achievements and Challenges Osama Shahid Seyedamin Pouriyeh R. Parizi Quan Z. Sheng Gautam Srivastava Liang Zhao FedML 89 77 0 23 Jul 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 80 663 0 20 May 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 277 274 0 26 Feb 2021
Scaling Federated Learning for Fine-tuning of Large Language Models Agrin Hilmkil Sebastian Callh Matteo Barbieri L. R. Sütfeld Edvin Listo Zec Olof Mogren FedML 48 49 0 01 Feb 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 316 725 0 31 Jan 2021
SparseDNN: Fast Sparse Deep Learning Inference on CPUs Ziheng Wang MQ 164 20 0 20 Jan 2021
SegBlocks: Block-Based Dynamic Resolution Networks for Real-Time Segmentation Thomas Verelst Tinne Tuytelaars SSeg 33 17 0 24 Nov 2020
Can Federated Learning Save The Planet? Xinchi Qiu Titouan Parcollet Daniel J. Beutel Taner Topal Akhil Mathur Nicholas D. Lane 57 81 0 13 Oct 2020
Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores Orestis Zachariadis Nitin Satpute Juan Gómez Luna J. Olivares 56 61 0 29 Sep 2020
SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference Ziheng Wang 82 68 0 26 Aug 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 140 820 0 28 Jul 2020
Federated Learning With Quantized Global Model Updates M. Amiri Deniz Gunduz Sanjeev R. Kulkarni H. Vincent Poor FedML 95 132 0 18 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 106 1,051 0 12 Jun 2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning Andrew Straiton Hard Kurt Partridge Cameron Nguyen Niranjan A. Subrahmanya Aishanee Shah Pai Zhu Ignacio López Moreno Rajiv Mathews OOD FedML 59 67 0 21 May 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 188 1,452 0 29 Feb 2020
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach Pengchao Han Shiqiang Wang K. Leung FedML 74 181 0 14 Jan 2020
Sparse Weight Activation Training Md Aamir Raihan Tor M. Aamodt 108 73 0 07 Jan 2020
Federated Learning with Personalization Layers Manoj Ghuhan Arivazhagan V. Aggarwal Aaditya Kumar Singh Sunav Choudhary FedML 96 840 0 02 Dec 2019
Fast Sparse ConvNets Erich Elsen Marat Dukhan Trevor Gale Karen Simonyan 174 153 0 21 Nov 2019
Model Pruning Enables Efficient Federated Learning on Edge Devices Yuang Jiang Shiqiang Wang Victor Valls Bongjun Ko Wei-Han Lee Kin K. Leung Leandros Tassiulas 110 465 0 26 Sep 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 150 1,164 0 13 Sep 2019
Importance Estimation for Neural Network Pruning Pavlo Molchanov Arun Mallya Stephen Tyree I. Frosio Jan Kautz 3DPC 89 885 0 25 Jun 2019
Bayesian Nonparametric Federated Learning of Neural Networks Mikhail Yurochkin Mayank Agarwal S. Ghosh Kristjan Greenewald T. Hoang Y. Khazaeni FedML 131 730 0 28 May 2019
Expanding the Reach of Federated Learning by Reducing Client Resource Requirements S. Caldas Jakub Konecný H. B. McMahan Ameet Talwalkar 95 450 0 18 Dec 2018
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 190 5,227 0 14 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 158 1,424 0 03 Dec 2018
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 138 1,546 0 08 Nov 2018
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks Yang He Guoliang Kang Xuanyi Dong Yanwei Fu Yi Yang AAML VLM 72 965 0 21 Aug 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 85 354 0 11 Jun 2018
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition Pete Warden 103 1,627 0 09 Apr 2018
SBNet: Sparse Blocks Network for Fast Inference Mengye Ren A. Pokrovsky Binh Yang R. Urtasun 125 180 0 07 Jan 2018
Hello Edge: Keyword Spotting on Microcontrollers Yundong Zhang Naveen Suda Liangzhen Lai Vikas Chandra 87 436 0 20 Nov 2017
NISP: Pruning Networks using Neuron Importance Score Propagation Ruichi Yu Ang Li Chun-Fu Chen Jui-Hsin Lai Vlad I. Morariu Xintong Han M. Gao Ching-Yung Lin L. Davis 74 800 0 16 Nov 2017
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression Jian-Hao Luo Jianxin Wu Weiyao Lin 58 1,761 0 20 Jul 2017
Channel Pruning for Accelerating Very Deep Neural Networks Yihui He Xiangyu Zhang Jian Sun 210 2,531 0 19 Jul 2017
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting Xu Sun Xuancheng Ren Shuming Ma Houfeng Wang 74 157 0 19 Jun 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 178 831 0 19 Jan 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 312 4,657 0 18 Oct 2016
Dynamic Network Surgery for Efficient DNNs Yiwen Guo Anbang Yao Yurong Chen 84 1,060 0 16 Aug 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 410 17,615 0 17 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,862 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 316 6,709 0 08 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,745 0 09 Mar 2015