On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond

6 August 2019

Papers citing "On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond"

9 / 9 papers shown

Title
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis Dachao Lin Yuze Han Haishan Ye Zhihua Zhang 25 11 0 15 Apr 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 29 10 0 15 Feb 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 34 2 0 09 Jan 2023
Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning Lin Zhang S. Shi Wei Wang Bo-wen Li 36 10 0 30 Jun 2022
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity D. Kovalev Aleksandr Beznosikov Ekaterina Borodich Alexander Gasnikov G. Scutari 36 12 0 30 May 2022
Acceleration in Distributed Optimization under Similarity Helena Lofstrom G. Scutari Tianyue Cao Alexander Gasnikov 24 26 0 24 Oct 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 27 630 0 20 May 2021
Newton Method over Networks is Fast up to the Statistical Precision Amir Daneshmand G. Scutari Pavel Dvurechensky Alexander Gasnikov 27 22 0 12 Feb 2021
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems Weijie Zhao Deping Xie Ronglai Jia Yulei Qian Rui Ding Mingming Sun P. Li MoE 59 150 0 12 Mar 2020