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L. Piras and Giacinto, G., Synthetic Pattern Generation for Imbalanced Learning in Image Retrieval, Pattern Recognition Letters, vol. 33, p. 7, 2012. (236.64 KB)
E. Costamagna, Fanni, A., and Giacinto, G., A Tabu Search algorithm for the optimisation of telecommunication networks, European Journal of Operational Research, vol. 106, pp. 357-372, 1998.
A. Fanni, Giacinto, G., Marchesi, M., and Serri, A., Tabu search coupled with deterministic strategies for the optimal design of MRI devices, Int. J. of Applied Electromagnetics and Mechanics, vol. 10, pp. 21-31, 1999.
L. Putzu, Piras, L., and Giacinto, G., Ten years of Relevance Score for Content Based Image Retrieval, in 14th International Conference Machine Learning and Data Mining (MLDM), New York, 2018, vol. 10935.
G. Giacinto and Roli, F., A theoretical framework for dynamic classifier selection, in 15th International Conference on Pattern Recognition, Barcelona, Spain, 2000, vol. 2, pp. 8-11.
D. Maiorca, Biggio, B., and Giacinto, G., Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks, ACM Computing Surveys, vol. 52, no. 4, 2019. (1.21 MB)
L. Piras and Giacinto, G., Unbalanced learning in Content-Based Image Classification and Retrieval, in IEEE International Conference on Multimedia & Expo (ICME), Singapore, 2010. (177.33 KB)
G. Giacinto, Roli, F., and Fumera, G., Unsupervised Learning of Neural Network Ensembles for Image Classification, in IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000), Como, Italy, 2000, vol. III, pp. 155-159.
L. Piras, Furcas, D., and Giacinto, G., User-driven Nearest-Neighbour Exploration of Image Archives, in 4th International Conference on Pattern Recognition Applications and Methods (ICPRAM), Lisbon, Portugal, 2015, pp. 181 - 189. (376.55 KB)
D. M. Freeman, Jain, S., Duermuth, M., Biggio, B., and Giacinto, G., Who Are You? A Statistical Approach to Measuring User Authenticity, in Proc. 23rd Annual Network & Distributed System Security Symposium (NDSS), 2016. (764.14 KB)
A. Demontis, Melis, M., Biggio, B., Maiorca, D., Arp, D., Rieck, K., Corona, I., Giacinto, G., and Roli, F., Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection, IEEE Trans. Dependable and Secure Computing, vol. 16, no. 4, pp. 711-724, 2019. (3.61 MB)
D. Ariu, Didaci, L., Fumera, G., Frumento, E., Freschi, F., and Giacinto, G., Yet Another Cybersecurity Roadmapping Methodology, in First International Workshop on Future Scenarios for Cybercrime and Cyber-terrorism, co-located with the 10th International Conference on Availability, Reliability and Security (ARES), 2015. (1.34 MB)