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The instabilities of large learning rate training: a loss landscape view

The instabilities of large learning rate training: a loss landscape view

Lawrence Wang
Stephen J. Roberts
ArXiv (abs)PDFHTML

Papers citing "The instabilities of large learning rate training: a loss landscape view"

5 / 5 papers shown
Title
Sharpness-Aware Minimization for Efficiently Improving Generalization
Sharpness-Aware Minimization for Efficiently Improving Generalization
Pierre Foret
Ariel Kleiner
H. Mobahi
Behnam Neyshabur
AAML
192
1,350
0
03 Oct 2020
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited
Wesley J. Maddox
Gregory W. Benton
A. Wilson
116
61
0
04 Mar 2020
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
283
8,904
0
25 Aug 2017
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond
Levent Sagun
Léon Bottou
Yann LeCun
UQCV
91
236
0
22 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
427
2,941
0
15 Sep 2016

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