Harnessing Increased Client Participation with Cohort-Parallel Federated Learning

24 May 2024

Papers citing "Harnessing Increased Client Participation with Cohort-Parallel Federated Learning"

25 / 25 papers shown

Title
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary B. Charles Nicole Mitchell Krishna Pillutla Michael Reneer Zachary Garrett FedML AI4CE 67 29 0 18 Jul 2023
Decentralized Learning Made Easy with DecentralizePy Akash Dhasade Anne-Marie Kermarrec Rafael Pires Rishi Sharma Milos Vujasinovic 30 15 0 17 Apr 2023
Decentralized Learning with Multi-Headed Distillation A. Zhmoginov Mark Sandler Nolan Miller Gus Kristiansen Max Vladymyrov FedML 63 4 0 28 Nov 2022
Auxo: Efficient Federated Learning via Scalable Client Clustering Jiachen Liu Fan Lai Yinwei Dai Aditya Akella H. Madhyastha Mosharaf Chowdhury 93 10 0 29 Oct 2022
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation Xuan Gong Abhishek Sharma Srikrishna Karanam Ziyan Wu Terrence Chen David Doermann Arun Innanje FedML 61 71 0 10 Sep 2022
Papaya: Practical, Private, and Scalable Federated Learning Dzmitry Huba John Nguyen Kshitiz Malik Ruiyu Zhu Michael G. Rabbat ... H. Srinivas Kaikai Wang Anthony Shoumikhin Jesik Min Mani Malek FedML 130 138 0 08 Nov 2021
Resource-Efficient Federated Learning A. Abdelmoniem Atal Narayan Sahu Marco Canini Suhaib A. Fahmy FedML 62 56 0 01 Nov 2021
Flexible Clustered Federated Learning for Client-Level Data Distribution Shift Moming Duan Duo Liu Xinyuan Ji Yu Wu Liang Liang Xianzhang Chen Yujuan Tan FedML OOD 58 112 0 22 Aug 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 49 112 0 15 Jun 2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing M. Khodak Renbo Tu Tian Li Liam Li Maria-Florina Balcan Virginia Smith Ameet Talwalkar FedML 81 78 0 08 Jun 2021
FedScale: Benchmarking Model and System Performance of Federated Learning at Scale Fan Lai Yinwei Dai Sanjay Sri Vallabh Singapuram Jiachen Liu Xiangfeng Zhu H. Madhyastha Mosharaf Chowdhury FedML 74 197 0 24 May 2021
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 76 1,031 0 12 Jun 2020
An Efficient Framework for Clustered Federated Learning Avishek Ghosh Jichan Chung Dong Yin Kannan Ramchandran FedML 49 850 0 07 Jun 2020
Federated learning with hierarchical clustering of local updates to improve training on non-IID data Christopher Briggs Zhong Fan Péter András FedML 59 566 0 24 Apr 2020
AI Benchmark: All About Deep Learning on Smartphones in 2019 Andrey D. Ignatov Radu Timofte Andrei Kulik Seungsoo Yang Ke Wang Felix Baum Max Wu Lirong Xu Luc Van Gool ELM 39 220 0 15 Oct 2019
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 84 845 0 08 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 130 982 0 04 Oct 2019
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 121 563 0 01 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 121 1,128 0 13 Sep 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 101 2,652 0 04 Feb 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 93 5,105 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 118 1,410 0 03 Dec 2018
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 251 17,328 0 17 Feb 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 286 19,523 0 09 Mar 2015
Convolutional Neural Networks Applied to House Numbers Digit Classification P. Sermanet Soumith Chintala Yann LeCun 76 543 0 18 Apr 2012