An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning

4 June 2021

Papers citing "An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning"

5 / 5 papers shown

Title
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 52 14 0 25 May 2023
Exploring Local Norms in Exp-concave Statistical Learning Nikita Puchkin Nikita Zhivotovskiy 86 2 0 21 Feb 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 41 2 0 09 Jan 2023
Private optimization in the interpolation regime: faster rates and hardness results Hilal Asi Karan N. Chadha Gary Cheng John C. Duchi 49 5 0 31 Oct 2022
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 182 683 0 07 Dec 2010