Nonconvex Federated Learning on Compact Smooth Submanifolds With
Heterogeneous Data

Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data

12 June 2024

Anthony Man-Cho So

Mikael Johansson

Papers citing "Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data"

15 / 15 papers shown

Title
Composite federated learning with heterogeneous data Jiaojiao Zhang Jiang Hu Mikael Johansson FedML 47 4 0 04 Sep 2023
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold Jun Chen Haishan Ye Mengmeng Wang Tianxin Huang Guangwen Dai Ivor W.Tsang Yang Liu 45 13 0 21 Aug 2023
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 49 6 0 06 Jun 2023
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models Nikolaos Dimitriadis P. Frossard Franccois Fleuret 62 25 0 18 Oct 2022
Federated Learning on Riemannian Manifolds Jiaxiang Li Shiqian Ma FedML 38 13 0 12 Jun 2022
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation Han Wang Siddartha Marella James Anderson FedML 32 40 0 28 Mar 2022
Distributed Principal Component Analysis with Limited Communication Foivos Alimisis Peter Davies Bart Vandereycken Dan Alistarh 47 12 0 27 Oct 2021
Decentralized Riemannian Gradient Descent on the Stiefel Manifold Shixiang Chen Alfredo García Mingyi Hong Shahin Shahrampour 60 45 0 14 Feb 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 79 159 0 14 Feb 2021
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 116 218 0 08 Aug 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 217 6,247 0 10 Dec 2019
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning Hao Yu Sen Yang Shenghuo Zhu MoMe FedML 73 605 0 17 Jul 2018
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation James Townsend Niklas Koep S. Weichwald 73 247 0 10 Mar 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 390 17,453 0 17 Feb 2016
Manopt, a Matlab toolbox for optimization on manifolds Nicolas Boumal Bamdev Mishra P.-A. Absil R. Sepulchre 97 1,029 0 23 Aug 2013