FedSplit: An algorithmic framework for fast federated optimization

11 May 2020

Papers citing "FedSplit: An algorithmic framework for fast federated optimization"

18 / 118 papers shown

Title
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications Xiang Li Zhihua Zhang 20 4 0 05 Jan 2021
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity Amirhossein Reisizadeh Isidoros Tziotis Hamed Hassani Aryan Mokhtari Ramtin Pedarsani FedML 162 98 0 28 Dec 2020
FedEval: A Holistic Evaluation Framework for Federated Learning Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang FedML 14 8 0 19 Nov 2020
Federated Composite Optimization Honglin Yuan Manzil Zaheer Sashank J. Reddi FedML 14 57 0 17 Nov 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 17 108 0 03 Nov 2020
Fast Convergence Algorithm for Analog Federated Learning Shuhao Xia Jingyang Zhu Yuhan Yang Yong Zhou Yuanming Shi Wei-Neng Chen FedML 22 31 0 30 Oct 2020
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms Maruan Al-Shedivat Jennifer Gillenwater Eric P. Xing Afshin Rostamizadeh FedML 6 109 0 11 Oct 2020
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 22 186 0 05 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies Yae Jee Cho Jianyu Wang Gauri Joshi FedML 25 399 0 03 Oct 2020
Robustness and Personalization in Federated Learning: A Unified Approach via Regularization Achintya Kundu Pengqian Yu L. Wynter Shiau Hong Lim FedML 6 14 0 14 Sep 2020
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent Rahif Kassab Osvaldo Simeone FedML 10 45 0 11 Sep 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 14 1,295 0 15 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods Zachary B. Charles Jakub Konecný FedML 12 54 0 02 Jul 2020
Federated Learning Meets Multi-objective Optimization Zeou Hu K. Shaloudegi Guojun Zhang Yaoliang Yu FedML 8 89 0 20 Jun 2020
Federated Accelerated Stochastic Gradient Descent Honglin Yuan Tengyu Ma FedML 9 171 0 16 Jun 2020
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 116 259 0 10 Dec 2012
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 166 683 0 07 Dec 2010