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Unpublished conference/Abstract (Scientific congresses and symposiums)
Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability
Ozbulak, Utku
;
Peck, Jonathan
;
De Neve, Wesley
et al.
2020
•
37th International Conference on Machine Learning: Workshop on Uncertainty & Robustness in Deep Learning (ICML UDL 2020)
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https://hdl.handle.net/2268/265032
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ICML2020-UDL-135.pdf
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Disciplines :
Computer science
Mathematics
Author, co-author :
Ozbulak, Utku
Peck, Jonathan
De Neve, Wesley
Goossens, Bart
Saeys, Yvan
Van Messem, Arnout
;
Université de Liège - ULiège > Département de mathématique > Statistique applquée aux sciences
Language :
English
Title :
Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability
Publication date :
2020
Event name :
37th International Conference on Machine Learning: Workshop on Uncertainty & Robustness in Deep Learning (ICML UDL 2020)
Event place :
Vienna, Austria
Event date :
Jul 12-18, 2020
Audience :
International
Available on ORBi :
since 15 November 2021
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36 (2 by ULiège)
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11 (2 by ULiège)
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