Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants
via the Mirror Stochastic Polyak Stepsize

Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize

28 October 2021

Ioannis Mitliagkas

Papers citing "Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize"

18 / 18 papers shown

Title
Primal-dual algorithm for contextual stochastic combinatorial optimization Louis Bouvier Thibault Prunet Vincent Leclère Axel Parmentier 35 0 0 07 May 2025
Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance Dimitris Oikonomou Nicolas Loizou 55 4 0 06 Jun 2024
Generalized Exponentiated Gradient Algorithms and Their Application to On-Line Portfolio Selection Andrzej Cichocki S. Cruces A. Sarmiento Toshihisa Tanaka 34 2 0 02 Jun 2024
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation Aaron Mishkin Mert Pilanci Mark Schmidt 62 1 0 03 Apr 2024
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad Sayantan Choudhury N. Tupitsa Nicolas Loizou Samuel Horváth Martin Takáč Eduard A. Gorbunov 30 1 0 05 Mar 2024
SANIA: Polyak-type Optimization Framework Leads to Scale Invariant Stochastic Algorithms Farshed Abdukhakimov Chulu Xiang Dmitry Kamzolov Robert Mansel Gower Martin Takáč 35 2 0 28 Dec 2023
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging C. Tsai Hao-Chung Cheng Yen-Huan Li 33 0 0 05 Nov 2023
Locally Adaptive Federated Learning Sohom Mukherjee Nicolas Loizou Sebastian U. Stich FedML 19 3 0 12 Jul 2023
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees Sharan Vaswani A. Kazemi Reza Babanezhad Nicolas Le Roux OffRL 27 3 0 24 May 2023
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions S. Choudhury Eduard A. Gorbunov Nicolas Loizou 25 13 0 27 Feb 2023
Low-rank Optimal Transport: Approximation, Statistics and Debiasing M. Scetbon Marco Cuturi OT 29 16 0 24 May 2022
Mirror Descent Strikes Again: Optimal Stochastic Convex Optimization under Infinite Noise Variance Nuri Mert Vural Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 15 23 0 23 Feb 2022
Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent -- an Open Problem Rémi Le Priol Frederik Kunstner Damien Scieur Simon Lacoste-Julien 11 1 0 12 Nov 2021
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu Jiayang Li Zhuoran Yang Hoi-To Wai Mingyi Hong Y. Nie Zhaoran Wang 60 18 0 04 Oct 2021
A Bregman Learning Framework for Sparse Neural Networks Leon Bungert Tim Roith Daniel Tenbrinck Martin Burger 16 17 0 10 May 2021
AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods Zheng Shi Abdurakhmon Sadiev Nicolas Loizou Peter Richtárik Martin Takávc ODL 32 13 0 19 Feb 2021
L4: Practical loss-based stepsize adaptation for deep learning Michal Rolínek Georg Martius ODL 36 63 0 14 Feb 2018
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 171 683 0 07 Dec 2010