ResearchTrend.AI
The advantages of multiple classes for reducing overfitting from test set reuse

The advantages of multiple classes for reducing overfitting from test set reuse

Vitaly Feldman
Roy Frostig
Moritz Hardt
ArXiv (abs)PDFHTML

Papers citing "The advantages of multiple classes for reducing overfitting from test set reuse"

5 / 5 papers shown
Title
Cold Case: The Lost MNIST Digits
Cold Case: The Lost MNIST Digits
Chhavi Yadav
Léon Bottou
61
106
0
25 May 2019
Do ImageNet Classifiers Generalize to ImageNet?
Do ImageNet Classifiers Generalize to ImageNet?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OODSSegVLM
113
1,715
0
13 Feb 2019
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Benjamin Recht
Rebecca Roelofs
Ludwig Schmidt
Vaishaal Shankar
OODFedMLELM
166
412
0
01 Jun 2018
The Ladder: A Reliable Leaderboard for Machine Learning Competitions
The Ladder: A Reliable Leaderboard for Machine Learning Competitions
Avrim Blum
Moritz Hardt
63
135
0
16 Feb 2015
Estimation in high dimensions: a geometric perspective
Estimation in high dimensions: a geometric perspective
Roman Vershynin
136
134
0
20 May 2014

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