Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis

25 July 2023

Papers citing "Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis"

19 / 19 papers shown

Title
Group Distributionally Robust Dataset Distillation with Risk Minimization Saeed Vahidian Mingyu Wang Jianyang Gu Vyacheslav Kungurtsev Wei Jiang Yiran Chen OOD DD 93 6 0 07 Feb 2024
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 64 12 0 14 Oct 2022
Semi-asynchronous Hierarchical Federated Learning for Cooperative Intelligent Transportation Systems Qimei Chen Zehua You Hao Jiang 38 13 0 18 Oct 2021
Distributionally Robust Federated Averaging Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 56 142 0 25 Feb 2021
Federated Reconstruction: Partially Local Federated Learning K. Singhal Hakim Sidahmed Zachary Garrett Shanshan Wu Keith Rush Sushant Prakash FedML 92 143 0 05 Feb 2021
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning Syed Zawad Ahsan Ali Pin-Yu Chen Ali Anwar Yi Zhou Nathalie Baracaldo Yuan Tian Feng Yan FedML 50 55 0 01 Feb 2021
Large-Scale Methods for Distributionally Robust Optimization Daniel Levy Y. Carmon John C. Duchi Aaron Sidford 81 217 0 12 Oct 2020
Advances in Asynchronous Parallel and Distributed Optimization By Mahmoud Assran Arda Aytekin Hamid Reza Feyzmahdavian M. Johansson Michael G. Rabbat 75 77 0 24 Jun 2020
A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems Zi Xu Hui-Li Zhang Yang Xu Guanghui Lan 89 101 0 03 Jun 2020
Robustness analytics to data heterogeneity in edge computing Jia Qian Lars Kai Hansen Xenofon Fafoutis Prayag Tiwari Hari Mohan Pandey FedML 53 4 0 12 Feb 2020
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 67 347 0 14 Oct 2019
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Daniel Kuhn Peyman Mohajerin Esfahani Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh OOD 64 395 0 23 Aug 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 93 211 0 21 Feb 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 139 940 0 01 Feb 2019
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 91 424 0 20 Oct 2018
Robust Optimization over Multiple Domains Qi Qian Shenghuo Zhu Jiasheng Tang Rong Jin Baigui Sun Hao Li OOD 82 71 0 19 May 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,928 0 25 Aug 2017
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
Asynchronous Distributed ADMM for Large-Scale Optimization- Part I: Algorithm and Convergence Analysis Tsung-Hui Chang Mingyi Hong Wei-Cheng Liao Xiangfeng Wang 57 200 0 09 Sep 2015