Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks

18 April 2023

Papers citing "Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks"

8 / 8 papers shown

Title
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 47 21 0 30 Mar 2022
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks Chaoyue Liu Libin Zhu M. Belkin ODL 73 262 0 29 Feb 2020
Unified Optimal Analysis of the (Stochastic) Gradient Method Sebastian U. Stich 54 113 0 09 Jul 2019
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 84 407 0 24 May 2019
Convergence rates for the stochastic gradient descent method for non-convex objective functions Benjamin J. Fehrman Benjamin Gess Arnulf Jentzen 80 101 0 02 Apr 2019
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD Zeyuan Allen-Zhu ODL 73 171 0 08 Jan 2018
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard Jason D. Lee 172 419 0 16 Jul 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 126 3,681 0 08 Jun 2017