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Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks

Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2566151819

Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks

About this item

Full title

Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2021-08

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

Scope and Contents

Contents

Adversarial defenses train deep neural networks to be invariant to the input perturbations from adversarial attacks. Almost all defense strategies achieve this invariance through adversarial training i.e. training on inputs with adversarial perturbations. Although adversarial training is successful at mitigating adversarial attacks, the behavioral...

Alternative Titles

Full title

Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2566151819

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2566151819

Other Identifiers

E-ISSN

2331-8422

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