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There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average

There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average

14 June 2018
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
ArXivPDFHTML

Papers citing "There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average"

3 / 53 papers shown
Title
Interpolation Consistency Training for Semi-Supervised Learning
Interpolation Consistency Training for Semi-Supervised Learning
Vikas Verma
Kenji Kawaguchi
Alex Lamb
Arno Solin
Arno Solin
Yoshua Bengio
David Lopez-Paz
39
756
0
09 Mar 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
Haowei He
Gao Huang
Yang Yuan
ODL
MLT
28
147
0
02 Feb 2019
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
308
2,890
0
15 Sep 2016
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