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  Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks

Stutz, D., Hein, M., & Schiele, B. (2020). Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks. In H. Daumé, & A. Singh (Eds.), Proceedings of the 37th International Conference on Machine Learning (pp. 9155-9166). Retrieved from http://proceedings.mlr.press/v119/stutz20a.html.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-AA75-6 Version Permalink: http://hdl.handle.net/21.11116/0000-0007-AA76-5
Genre: Conference Paper
Latex : Confidence-Calibrated Adversarial Training: {G}eneralizing to Unseen Attacks

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 Creators:
Stutz, David1, Author              
Hein, Matthias2, Author
Schiele, Bernt1, Author              
Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published online
 Pages: 12 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: DBLP:conf/icml/Stutz0S20
URI: http://proceedings.mlr.press/v119/stutz20a.html
 Degree: -

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Title: 37th International Conference on Machine Learning
Place of Event: Virtual Conference
Start-/End Date: 2020-07-13 - 2020-07-18

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Source 1

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Title: Proceedings of the 37th International Conference on Machine Learning
  Abbreviation : ICML 2020
Source Genre: Proceedings
 Creator(s):
Daumé, Hal1, Editor
Singh, Aarti1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 9155 - 9166 Identifier: -

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Title: Proceedings of Machine Learning Research
  Abbreviation : PMLR
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 119 Sequence Number: - Start / End Page: - Identifier: ISSN: 1938-7228