Publications
Journal papers
D. Faccini, F. Maggioni, F. A. Potra (2022). Robust and distributionally robust optimization models for Linear Support Vector Machine. Computers and Operations Research 147, 105930. DOI: https://doi.org/10.1016/j.cor.2022.105930
X. Chou, E. Messina (2023). Problem-Driven Scenario Generation for Stochastic Programming Problems: A Survey. Algorithms 16 (10), 479. DOI: https://doi.org/10.3390/a16100479
G. Bayraksan, F. Maggioni, D. Faccini, M. Yang (2024). Bounds for Multistage Mixed Integer Distributionally Robust Optimization. Siam Journal on Optimization 34 (1). DOI: https://doi.org/10.1137/22M147178X
E. Fadda, D. Manerba, R. Tadei. How to locate services optimizing redundancy: A comparative analysis of K-Covering Facility Location models. Socio-Economic Planning Sciences 94, 101938. DOI: https://doi.org/10.1016/j.seps.2024.101938
Conference Proceedings and Book Chapters
M. Bierlaire, E. Fadda, L. Fotio Tiotsop, D. Manerba (2022). A chance-constraint approach for optimizing social engagement-based services. Proceedings of the 17th Conference on Computer Science and Intelligence Systems (FedCSIS), pp. 301-304. Sofia, Bulgaria. DOI: https://doi.org/10.15439/2022F235
E. Fersini, S. Mottadelli, M. Carbonera, E. Messina (2022). Deep Attributed Graph Embeddings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13408 LNAI, pp. 181-192. DOI: https://doi.org/10.1007/978-3-031-13448-7_15
M. Carbonera, M. Ciavotta, E. Messina (2023). Driving into Uncertainty: An Adversarial Generative Approach for Multivariate Scenario Generation. Proceedings of the IEEE International Conference on Big Data (BigData), pp. 2578-2587. DOI: http://dx.doi.org/10.1109/BigData59044.2023.10386128
S. Fiorini, S. Coniglio, M. Ciavotta, E. Messina (2023). SigMaNet: One Laplacian to Rule Them All. Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, 37. pp. 7568–7576. DOI: https://doi.org/10.48550/arXiv.2205.13459
R. De Leone, F. Maggioni, A. Spinelli (2024). A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions. In: Nicosia, G., Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P.M., Umeton, R. (eds) Machine Learning, Optimization, and Data Science. LOD 2023. Lecture Notes in Computer Science, vol 14506. Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-53966-4_22
F. Maggioni, A. Spinelli (2024). Vehicles Smog Rating Classification using a New Robust Support Vector Machine Approach. In: Optimization in Green Sustainability and Ecological Transition, AIRO Springer Series, ch. 19. DOI: https://doi.org/10.1007/978-3-031-47686-0_19
D. Bezzi, O. Jabali, F. Maggioni (2024). A Threshold Recourse Policy for the Electric Vehicle Routing Problem with Stochastic Energy Consumption. In: Optimization in Green Sustainability and Ecological Transition, AIRO Springer Series, ch. 20. DOI: https://doi.org/10.1007/978-3-031-47686-0_20
S. Fiorini, S. Coniglio, M. Ciavotta, E. Messina (to appear). Graph Learning in 4D: A Quaternion-Valued Laplacian to Enhance Spectral GCNs. Proceedings of the 38th AAAI Conference on Artificial Intelligence, AAAI 2024. DOI: https://doi.org/10.48550/arXiv.2312.17361