Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy

7 February 2023

Papers citing "Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy"

8 / 8 papers shown

Title
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity Dmitry Bylinkin Aleksandr Beznosikov 72 1 0 21 Dec 2024
SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning Avetik G. Karagulyan Egor Shulgin Abdurakhmon Sadiev Peter Richtárik FedML 35 2 0 30 May 2024
Non-Convex Stochastic Composite Optimization with Polyak Momentum Yuan Gao Anton Rodomanov Sebastian U. Stich 21 6 0 05 Mar 2024
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods El Mahdi Chayti N. Doikov Martin Jaggi ODL 19 5 0 23 Feb 2023
Target-based Surrogates for Stochastic Optimization J. Lavington Sharan Vaswani Reza Babanezhad Mark W. Schmidt Nicolas Le Roux 38 5 0 06 Feb 2023
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity D. Kovalev Aleksandr Beznosikov Ekaterina Borodich Alexander Gasnikov G. Scutari 28 12 0 30 May 2022
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 65 317 0 18 Feb 2014
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 166 683 0 07 Dec 2010