Lower Bounds and Optimal Algorithms for Personalized Federated Learning

Lower Bounds and Optimal Algorithms for Personalized Federated Learning

5 October 2020

Slavomír Hanzely

Samuel Horváth

Peter Richtárik

Papers citing "Lower Bounds and Optimal Algorithms for Personalized Federated Learning"

14 / 114 papers shown

Title
QuPeL: Quantized Personalization with Applications to Federated Learning Kaan Ozkara Navjot Singh Deepesh Data Suhas Diggavi FedML 22 5 0 23 Feb 2021
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely Boxin Zhao Mladen Kolar FedML 19 52 0 19 Feb 2021
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization Canh T. Dinh Thanh Tung Vu N. H. Tran Minh N. Dao Hongyu Zhang FedML 65 40 0 14 Feb 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 87 945 0 03 Feb 2021
FedEval: A Holistic Evaluation Framework for Federated Learning Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang FedML 25 8 0 19 Nov 2020
Federated Composite Optimization Honglin Yuan Manzil Zaheer Sashank J. Reddi FedML 24 57 0 17 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 19 0 0 26 Aug 2020
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning) El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Arsany Guirguis L. Hoang Sébastien Rouault FedML 8 63 0 03 Aug 2020
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 188 542 0 30 Mar 2020
Survey of Personalization Techniques for Federated Learning V. Kulkarni Milind Kulkarni Aniruddha Pant FedML 171 326 0 19 Mar 2020
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Q. Li Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 20 968 0 23 Jul 2019
SecureBoost: A Lossless Federated Learning Framework Kewei Cheng Tao Fan Yilun Jin Yang Liu Tianjian Chen Dimitrios Papadopoulos Qiang Yang FedML 14 578 0 25 Jan 2019
Distributed Stochastic Multi-Task Learning with Graph Regularization Weiran Wang Jialei Wang Mladen Kolar Nathan Srebro FedML 29 21 0 11 Feb 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 302 11,681 0 09 Mar 2017