On the Convergence of Step Decay Step-Size for Stochastic Optimization

18 February 2021

Papers citing "On the Convergence of Step Decay Step-Size for Stochastic Optimization"

6 / 6 papers shown

Title
Increasing Both Batch Size and Learning Rate Accelerates Stochastic Gradient Descent Hikaru Umeda Hideaki Iiduka 59 2 0 17 Feb 2025
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 17 1 0 19 Jan 2024
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 18 0 0 19 Oct 2023
Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods Junchi Yang Xiang Li Ilyas Fatkhullin Niao He 26 15 0 21 May 2023
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 111 259 0 10 Dec 2012
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 570 0 08 Dec 2012