Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters

26 August 2020

Papers citing "Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters"

5 / 5 papers shown

Title
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 47 30 0 13 Feb 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 237 11,568 0 09 Mar 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,190 0 16 Aug 2016
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 76 736 0 19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 60 317 0 18 Feb 2014