Foto del docente

Michela Milano

Professoressa ordinaria

Dipartimento di Informatica - Scienza e Ingegneria

Settore scientifico disciplinare: ING-INF/05 SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI

Direttrice Centro Interdipartimentale Alma Mater Research Institute for Human-Centered Artificial Intelligence — (Alma AI)

Pubblicazioni

Borghesi A.; Molan M.; Milano M.; Bartolini A., Anomaly Detection and Anticipation in High Performance Computing Systems, «IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS», 2022, 33, pp. 739 - 750 [articolo]Open Access

Lombardi, Michele; Baldo, Federico; Borghesi, Andrea; Milano, Michela, An Analysis of Regularized Approaches for Constrained Machine Learning, in: Trustworthy AI - Integrating Learning, Optimization and Reasoning. TAILOR 2020., Cham, Springer, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2021, 12641, pp. 112 - 119 (atti di: 1st International Workshop on Trustworthy AI – Integrating Learning, Optimization and Reasoning, TAILOR 2020 held as a part of European Conference on Artificial Intelligence, ECAI 2020, Online, 4-5 September 2020) [Contributo in Atti di convegno]Open Access

Silvestri M.; Lombardi M.; Milano M., Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Science and Business Media Deutschland GmbH, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2021, 12735, pp. 266 - 282 (atti di: 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, Vienna, Austria, 2021) [Contributo in Atti di convegno]

De Filippo, Allegra; Lombardi, Michele; Milano, Michela, Integrated Offline and Online Decision Making under Uncertainty, «THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH», 2021, 70, pp. 77 - 117 [articolo]Open Access

Fabrizio Detassis, Michele Lombardi, Michela Milano, Teaching the Old Dog New Tricks: Supervised Learning with Constraints, in: Thirty-Fifth {AAAI} Conference on Artificial Intelligence, {AAAI}2021, Thirty-Third Conference on Innovative Applications of ArtificialIntelligence, {IAAI} 2021, The Eleventh Symposium on Educational Advancesin Artificial Intelligence, {EAAI} 2021, Virtual Event, February 2-9,2021, {AAAI} Press, «PROCEEDINGS OF THE ... AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE», 2021, 35, pp. 3742 - 3749 (atti di: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual event, 2-9 February) [Contributo in Atti di convegno]

Borghesi, Andrea; Tagliavini, Giuseppe; Lombardi, Michele; Benini, Luca; Milano, Michela, Combining learning and optimization for transprecision computing, in: Proceedings of the 17th ACM International Conference on Computing Frontiers, 2020, pp. 10 - 18 (atti di: 17th ACM International Conference on Computing Frontiers, Catania, Italy, 1-10 June 2020) [Contributo in Atti di convegno]Open Access

De Filippo A.; Lombardi M.; Milano M., Hybrid offline/online optimization under uncertainty, in: Frontiers in Artificial Intelligence and Applications, IOS Press BV, «FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS», 2020, 325, pp. 2899 - 2900 (atti di: 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020, esp, 2020) [Contributo in Atti di convegno]Open Access

Silvestri M.; Lombardi M.; Milano M., Injecting domain knowledge in neural networks: A controlled experiment on a constrained problem, in: CEUR Workshop Proceedings, CEUR-WS, «CEUR WORKSHOP PROCEEDINGS», 2020, 2659, pp. 52 - 58 (atti di: 1st International Workshop on New Foundations for Human-Centered AI, NeHuAI 2020, esp, 2020) [Contributo in Atti di convegno]

Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano, Injective Domain Knowledge in Neural Networks for Transprecision Computing, in: Machine Learning, Optimization, and Data Science - 6th InternationalConference, LOD 2020, Siena, Italy, July 19-23, 2020, Revised Selected Papers, Part I, Springer, 2020, 12565, pp. 587 - 600 (atti di: The Sixth International Conference on Machine Learning, Optimization, and Data Science, Siena, July 19-23, 2020) [Contributo in Atti di convegno]

Detassis F.; Lombardi M.; Milano M., Teaching the old dog new tricks: Supervised learning with constraints, in: CEUR Workshop Proceedings, Aachen, CEUR-WS, «CEUR WORKSHOP PROCEEDINGS», 2020, 2659, pp. 44 - 51 (atti di: 1st International Workshop on New Foundations for Human-Centered AI, NeHuAI 2020, esp, 2020) [Contributo in Atti di convegno]Open Access

De Filippo A.; Lombardi M.; Milano M., The blind men and the elephant: Integrated offline/online optimization under uncertainty, in: PROCEEDINGS OF THE TWENTY-NINTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, International Joint Conferences on Artificial Intelligence, 2020, 2021-, pp. 4840 - 4846 (atti di: 29th International Joint Conference on Artificial Intelligence, IJCAI 2020, jpn, 2021) [Contributo in Atti di convegno]Open Access

Chisca D.S.; Lombardi M.; Milano M.; O'Sullivan B., A Sampling-Free Anticipatory Algorithm for the Kidney Exchange Problem, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2019, 11494, pp. 146 - 162 (atti di: 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2019, grc, 2019) [Contributo in Atti di convegno]

Borghesi A.; Bartolini A.; Lombardi M.; Milano M.; Benini L., A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems, «ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE», 2019, 85, pp. 634 - 644 [articolo]Open Access

Borghesi, Andrea; Bartolini, Andrea; Lombardi, Michele; Milano, Michela; Benini, Luca, Anomaly Detection Using Autoencoders in High Performance Computing Systems, in: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019, 33, pp. 9428 - 9433 (atti di: Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, US, 28 Jan - 02 Feb 2019) [Contributo in Atti di convegno]

Borghesi, Andrea; Milano, Michela; Benini, Luca, Frequency Assignment in High Performance Computing Systems, in: Proceedings of the XVIIIth International Conference of the Italian Association for Artificial Intelligence, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2019, 11946, pp. 151 - 164 (atti di: XVIIIth International Conference of the Italian Association for Artificial Intelligence, Rende, Italy, November 19–22, 2019) [Contributo in Atti di convegno]

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