Marco Melis

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Battista BiggioFull Professor, University of Cagliari, ItalyEmail verificata su unica.it
Fabio RoliProfessor, University of Genova and Cagliari, ItalyEmail verificata su unige.it
Ambra DemontisAssistant Professor at University of CagliariEmail verificata su unica.it
Maura PintorUniversity of CagliariEmail verificata su unica.it
Giorgio FumeraAssociate Professor of Computer Engineering, University of CagliariEmail verificata su unica.it
Davide MaiorcaAssociate Professor of Computer Engineering at University of Cagliari, ItalyEmail verificata su unica.it
Alina OpreaNortheastern UniversityEmail verificata su neu.edu
Angelo SotgiuAssistant Professor, University of CagliariEmail verificata su unica.it
Igino CoronaComputer Security Researcher & Co-founder, Pluribus OneEmail verificata su pluribus-one.it
Konrad RieckTechnische Universität BerlinEmail verificata su tu-berlin.de
Daniel ArpTechnische Universität WienEmail verificata su tuwien.ac.at
Gavin BrownProfessor of Machine Learning, Dept of Computer Science, University of ManchesterEmail verificata su manchester.ac.uk
Michele ScalasPhDEmail verificata su avanade.com
Davide BacciuProfessor @ Università di Pisa - Founder & Chief Scientist @ ContinualIST.comEmail verificata su di.unipi.it
Francesco CrecchiPhD student in Computer Science, University of PisaEmail verificata su di.unipi.it
Luca PirasCo-Founder of Pluribus One, Research Assistant @ University of CagliariEmail verificata su pluribus-one.it
Luca DemetrioAssistant Professor at Università degli Studi di GenovaEmail verificata su unige.it

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Marco Melis

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Email verificata su unica.it - Home page

Adversarial Machine Learning Interpretability Computer Security Biometrics


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	501	2019
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 16 (4), 711-724, 2017	368	2017
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	125	2017
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	79	2018
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	73	2019
Secml: Secure and Explainable Machine Learning in Python M Melis, A Demontis, M Pintor, A Sotgiu, L Demetrio, B Biggio Available at SSRN 4003262, 2022	55*	2022
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 International Journal of Machine Learning and Cybernetics, 1-16, 2021	37	2021
Fader: Fast adversarial example rejection F Crecchi, M Melis, A Sotgiu, D Bacciu, B Biggio Neurocomputing 470, 257-268, 2022	24	2022
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	9	2016
Sparse Support Faces B Biggio, M Melis, G Fumera, F Roli Int'l Conf. on Biometrics (ICB), 208-213, 2015	5	2015
Explaining Vulnerability of Machine Learning to Adversarial Attacks M Melis Università degli Studi di Cagliari, 2021	4	2021
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	4	2015

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