Publications
, «Diversified Sensitivity based Undersampling for Imbalance Classification Problems», IEEE Transactions on Cybernetics, In Press.
(1.91 MB)
(1.91 MB), «On Reducing the Effect of Covariate Factors in Gait Recognition: a Classifier Ensemble Method», IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press. (311.43 KB) (151.4 KB)
(311.43 KB) (151.4 KB), «Scene-specific Crowd Counting Using Synthetic Training Images», Pattern Recognition, In Press. (3.14 MB)
(3.14 MB), «Explainability-Based Debugging of Machine Learning for Vulnerability Discovery», in Proc. 17th International Conference on Availability, Reliability and Security, New York, NY, USA, 2022.
, «FADER: Fast adversarial example rejection», Neurocomputing, vol 470, pagg 257-268, 2022.
, «secml: A Python Library for Secure and Explainable Machine Learning», SoftwareX, 2022.
, «Towards learning trustworthily, automatically, and with guarantees on graphs: An overview», Neurocomputing, vol 493, pagg 217-243, 2022.
, «Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection», ACM Trans. Priv. Secur., vol 24, 2021.
, «Adversarial Machine Learning: Attacks From Laboratories to the Real World», Computer, vol 54, pagg 56-60, 2021.
, «Automatic Myelofibrosis Grading from Silver-Stained Images», in Computer Analysis of Images and Patterns, Cham, 2021, pagg 195–205.
, «On the Effectiveness of Leukocytes Classification Methods in a Real Application Scenario», AI, vol 2, pagg 394–412, 2021.
, «Empirical Assessment of Generating Adversarial Configurations for Software Product Lines», Empirical Software Engineering, vol 26, n° 6, 2021. (1.29 MB)
(1.29 MB), «Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints», in NeurIPS, 2021.
, «Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware», IEEE Transactions on Information Forensics and Security, vol 16, pagg 3469-3478, 2021.
, «The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?», in International Joint Conference on Neural Networks, (IJCNN) 2021, Shenzhen, China, 2021, pagg 1–8.
, «How Realistic Should Synthetic Images Be for Training Crowd Counting Models?», in Computer Analysis of Images and Patterns, Cham, 2021, pagg 46–56.
, «Invariant Moments, Textural and Deep Features for Diagnostic MR and CT Image Retrieval», in Computer Analysis of Images and Patterns, Cham, 2021, pagg 287–297.
, «Poisoning Attacks on Algorithmic Fairness», in Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020), 2021, pag 162--177. (1.05 MB)
(1.05 MB), «Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems», in Proceedings of the 36th Annual ACM Symposium on Applied Computing, New York, NY, USA, 2021, pagg 116–125.
, «Adversarial Detection of Flash Malware: Limitations and Open Issues», Computers & Security, vol 96, 2020. (1.08 MB)
(1.08 MB), «Convolutional neural networks for relevance feedback in content based image retrieval: A Content based image retrieval system that exploits convolutional neural networks both for feature extraction and for relevance feedback», Multimedia Tools and Applications, vol 79, pagg 26995-27021, 2020.
, «Deep Neural Rejection against Adversarial Examples», EURASIP Journal on Information Security, vol 5, 2020.
, «Detection of red and white blood cells from microscopic blood images using a region proposal approach», Computers in Biology and Medicine, vol 116, 2020.
, «An Empirical Evaluation of Cross-scene Crowd Counting Performance», in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP, Valletta - Malta, 2020, vol 4, pagg 373-380. (527.29 KB)
(527.29 KB), «An empirical evaluation of nuclei segmentation from H&E images in a real application scenario», Applied Sciences (Switzerland), vol 10, pagg 1-15, 2020.
