Towards Model Agnostic Federated Learning Using Knowledge Distillation

28 October 2021

Papers citing "Towards Model Agnostic Federated Learning Using Knowledge Distillation"

35 / 35 papers shown

Title
FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated Clients Leming Shen Qiang Yang Kaiyan Cui Yuanqing Zheng Xiao-Yong Wei Jianwei Liu Jinsong Han FedML 148 11 0 28 Feb 2025
Beyond Model Scale Limits: End-Edge-Cloud Federated Learning with Self-Rectified Knowledge Agglomeration Zhiyuan Wu Sheng Sun Yuwei Wang Min Liu Ke Xu Quyang Pan Bo Gao Tian Wen FedML 39 1 0 03 Jan 2025
FedICT: Federated Multi-task Distillation for Multi-access Edge Computing Zhiyuan Wu Sheng Sun Yuwei Wang Min Liu Quyang Pan Xue Jiang Bo Gao 67 32 0 01 Jan 2023
Fed2: Feature-Aligned Federated Learning Fuxun Yu Weishan Zhang Zhuwei Qin Zirui Xu Di Wang Chenchen Liu Zhi Tian Xiang Chen FedML 46 76 0 28 Nov 2021
Optimal Model Averaging: Towards Personalized Collaborative Learning Felix Grimberg Mary-Anne Hartley Sai Praneeth Karimireddy Martin Jaggi FedML MoMe 33 15 0 25 Oct 2021
FedKD: Communication Efficient Federated Learning via Knowledge Distillation Chuhan Wu Fangzhao Wu Lingjuan Lyu Yongfeng Huang Xing Xie FedML 46 383 0 30 Aug 2021
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning Kaan Ozkara Navjot Singh Deepesh Data Suhas Diggavi FedML MQ 61 57 0 29 Jul 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 244 415 0 14 Jul 2021
Towards Understanding Knowledge Distillation Mary Phuong Christoph H. Lampert 50 314 0 27 May 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu Yuanzhi Li FedML 97 362 0 17 Dec 2020
Communication-Efficient Federated Distillation Felix Sattler Arturo Marbán R. Rischke Wojciech Samek FedML DD 51 35 0 01 Dec 2020
Federated Knowledge Distillation Hyowoon Seo Jihong Park Seungeun Oh M. Bennis Seong-Lyun Kim FedML 43 92 0 04 Nov 2020
A Closer Look at Codistillation for Distributed Training Shagun Sodhani Olivier Delalleau Mahmoud Assran Koustuv Sinha Nicolas Ballas Michael G. Rabbat 81 8 0 06 Oct 2020
Practical One-Shot Federated Learning for Cross-Silo Setting Qinbin Li Bingsheng He D. Song FedML 36 114 0 02 Oct 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning Sai Praneeth Karimireddy Martin Jaggi Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 56 216 0 08 Aug 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 47 1,026 0 12 Jun 2020
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 44 2,907 0 09 Jun 2020
Why distillation helps: a statistical perspective A. Menon A. S. Rawat Sashank J. Reddi Seungyeon Kim Sanjiv Kumar FedML 44 22 0 21 May 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 278 549 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 80 1,417 0 29 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 93 569 0 25 Feb 2020
Self-Distillation Amplifies Regularization in Hilbert Space H. Mobahi Mehrdad Farajtabar Peter L. Bartlett 52 231 0 13 Feb 2020
Understanding and Improving Knowledge Distillation Jiaxi Tang Rakesh Shivanna Zhe Zhao Dong Lin Anima Singh Ed H. Chi Sagar Jain 40 131 0 10 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 98 6,177 0 10 Dec 2019
Federated Evaluation of On-device Personalization Kangkang Wang Rajiv Mathews Chloé Kiddon Hubert Eichner F. Beaufays Daniel Ramage FedML 33 283 0 22 Oct 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 39 345 0 14 Oct 2019
Model Fusion via Optimal Transport Sidak Pal Singh Martin Jaggi MoMe FedML 65 231 0 12 Oct 2019
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 197 1,692 0 14 Apr 2018
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 314 405 0 09 Apr 2018
Deep Mutual Learning Ying Zhang Tao Xiang Timothy M. Hospedales Huchuan Lu FedML 102 1,645 0 01 Jun 2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning Ashia Wilson Rebecca Roelofs Mitchell Stern Nathan Srebro Benjamin Recht ODL 46 1,023 0 23 May 2017
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 43 499 0 14 Nov 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 223 17,235 0 17 Feb 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 169 19,448 0 09 Mar 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 755 99,991 0 04 Sep 2014