Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized
Learning: Part I

Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I

IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022

19 January 2022

Anthony Man-Cho So

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Papers citing "Variance-Reduced Stochastic Quasi-Newton Methods for Decentralized Learning: Part I"

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Review of Mathematical Optimization in Federated Learning Shusen Yang Fangyuan Zhao Zihao Zhou Liang Shi Xuebin Ren Zongben Xu FedML AI4CE 271 5 0 02 Dec 2024
Decentralized Riemannian natural gradient methods with Kronecker-product approximations Jiang Hu Kangkang Deng Na Li Shijie Zhao 142 9 0 16 Mar 2023
A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy EvaluationIEEE Transactions on Automatic Control (TAC), 2022 Sheng Zhang A. Pananjady Justin Romberg OffRL 230 4 0 23 Jul 2022
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimizationComputational optimization and applications (Comput. Optim. Appl.), 2022 Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 189 2 0 17 Jul 2022