Marco Melis
Title
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Cited by
Year
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
A Demontis, M Melis, B Biggio, D Maiorca, D Arp, K Rieck, I Corona, ...
IEEE Transactions on Dependable and Secure Computing, 2017
1172017
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ...
28th USENIX Security Symposium (USENIX Security 19), 321--338, 2019
63*2019
Is deep learning safe for robot vision? adversarial examples against the icub humanoid
M Melis, A Demontis, B Biggio, G Brown, G Fumera, F Roli
Proceedings of the IEEE International Conference on Computer Vision†…, 2017
472017
Explaining Black-box Android Malware Detection
M Melis, D Maiorca, B Biggio, G Giacinto, F Roli
2018 26th European Signal Processing Conference (EUSIPCO), pp. 524-528, 2018
172018
secml: A Python Library for Secure and Explainable Machine Learning
M Melis, A Demontis, M Pintor, A Sotgiu, B Biggio
arXiv preprint arXiv:1912.10013, 2019
52019
Sparse Support Faces
B Biggio, M Melis, G Fumera, F Roli
Int'l Conf. on Biometrics (ICB), 208-213, 2015
52015
Fast Image Classification with Reduced Multiclass Support Vector Machines
M Melis, L Piras, B Biggio, G Giacinto, G Fumera, F Roli
International Conference on Image Analysis and Processing, 78-88, 2015
32015
Deep Neural Rejection against Adversarial Examples
A Sotgiu, A Demontis, M Melis, B Biggio, G Fumera, X Feng, F Roli
EURASIP Journal on Information Security 2020, 1--10, 2019
22019
Super-Sparse Learning in Similarity Spaces
A Demontis, M Melis, B Biggio, G Fumera, F Roli
IEEE Computational Intelligence Magazine 11 (4), 36-45, 2016
22016
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?
M Melis, M Scalas, A Demontis, D Maiorca, B Biggio, G Giacinto, F Roli
arXiv preprint arXiv:2005.01452, 2020
12020
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