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Paper published in a book (Scientific congresses and symposiums)
How the Softmax Output is Misleading for Evaluating the Strength of Adversarial Examples
Ozbulak, Utku
;
De Neve, Wesley
;
Van Messem, Arnout
2018
•
In
NeuRIPS 2018: 32nd Conference on Neural Information Processing Systems; Workshop on Security in Machine Learning (SECML2018)
Peer reviewed
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https://hdl.handle.net/2268/257831
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Disciplines :
Computer science
Author, co-author :
Ozbulak, Utku
De Neve, Wesley
Van Messem, Arnout
;
Université de Liège - ULiège > Département de mathématique > Statistique applquée aux sciences
Language :
English
Title :
How the Softmax Output is Misleading for Evaluating the Strength of Adversarial Examples
Publication date :
2018
Event name :
32nd Conference on Neural Information Processing Systems (NeurIPS): Workshop on Security in Machine Learning (SECML)
Event place :
Montreal, Canada
Event date :
2018
Audience :
International
Main work title :
NeuRIPS 2018: 32nd Conference on Neural Information Processing Systems; Workshop on Security in Machine Learning (SECML2018)
Peer reviewed :
Peer reviewed
Additional URL :
https://arxiv.org/abs/1811.08577
Available on ORBi :
since 10 March 2021
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