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Improving the Robustness and Generalization of Deep Neural Network with
  Confidence Threshold Reduction

Improving the Robustness and Generalization of Deep Neural Network with Confidence Threshold Reduction

2 June 2022
Xiangyuan Yang
Jie Lin
Hanlin Zhang
Xinyu Yang
Peng Zhao
    AAML
    OOD
ArXivPDFHTML

Papers citing "Improving the Robustness and Generalization of Deep Neural Network with Confidence Threshold Reduction"

5 / 5 papers shown
Title
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
Hieu H. Pham
Quoc V. Le
66
56
0
05 Jan 2021
Dropout: Explicit Forms and Capacity Control
Dropout: Explicit Forms and Capacity Control
R. Arora
Peter L. Bartlett
Poorya Mianjy
Nathan Srebro
55
37
0
06 Mar 2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning
TaskNorm: Rethinking Batch Normalization for Meta-Learning
J. Bronskill
Jonathan Gordon
James Requeima
Sebastian Nowozin
Richard E. Turner
66
89
0
06 Mar 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
281
5,833
0
08 Jul 2016
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,634
0
03 Jul 2012
1