Silvestri M.; De Filippo A.; Ruggeri F.; Lombardi M., Hybrid Offline/Online Optimization for Energy Management via Reinforcement Learning, in: International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022, 13292 LNCS, pp. 358 - 373 (atti di: International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Los Angeles, 20-23 giugno 2022) [Contributo in Atti di convegno]
Federico Baldo, Michele Iannello, Michele Lombardi, Michela Milano, Informed Deep Learning for Epidemics Forecasting, in: Frontiers in Artificial Intelligence and Applications, IOS Press BV, «FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS», 2022, 351, pp. 86 - 99 (atti di: 11th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2022, co-located with the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence, IJCAI-ECAI 2022, aut, 2022) [Contributo in Atti di convegno]
Magnini A.; Lombardi M.; Persiano S.; Tirri A.; Lo Conti F.; Castellarin A., Machine-learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains, «NATURAL HAZARDS AND EARTH SYSTEM SCIENCES», 2022, 22, pp. 1469 - 1486 [articolo]Open Access
Mattia Silvestri, Michele Lombardi, Emiliano Mucchi, Luca Cadei, Giovanna Magnago, Marco Piantanida, Valentina D'Ottavio, Nguyen Van Tu, Simona Duma, Silvia Taddei, Annagiulia Tiozzo, Andrea Corneo, Lorenzo Lancia, Laura Rocchi, Pietro Coffari di Gilferraro, Supervised Anomaly Detection in Crude Oil Stabilization, in: Proceedings of PAIS 2022, «FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS», 2022, 351, pp. 114 - 127 (atti di: PAIS 2022, Vienna, Austria, 25 July 2022) [Contributo in Atti di convegno]
Seravalli A.; Busani M.; Venturi S.; Brutti A.; Petrovich C.; Frascella A.; Paolucci F.; Di Felice M.; Lombardi M.; Bellodi E.; Zese R.; Bertasi F.; Balugani E.; Cecaj A.; Gamberini R.; Mamei M.; Picone M., Towards Smart Cities for Tourism: the POLIS-EYE Project, in: Proceedings of ISC 2022, 2022, pp. 1 - 7 (atti di: ISC 2022, Pafos, Cyprus, September 26-29, 2022) [Contributo in Atti di convegno]
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
Maxime Mulamba,
Jayanta Mandi,
Michelangelo Diligenti,
Michele Lombardi,
Victor Bucarey,
Tias Guns, Contrastive Losses and Solution Caching for Predict-and-Optimize, in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, ijcai.org, 2021, pp. 2833 - 2840 (atti di: Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August) [Contributo in Atti di convegno]
Silvestri M.; Lombardi M.; Milano M., Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem, in: Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 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, 5 - 8 July 2021) [Contributo in Atti di convegno]Open Access
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
Fioretto F.; Van Hentenryck P.; Mak T.W.K.; Tran C.; Baldo F.; Lombardi M., Lagrangian Duality for Constrained Deep Learning, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, Springer Science and Business Media Deutschland GmbH, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2021, 12461, pp. 118 - 135 (atti di: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, Ghent, Belgium, 2020) [Contributo in Atti di convegno]
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, Santiago de Compostella, Spain, September 4, 2020) [Contributo in Atti di convegno]Open Access
Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano, Injective Domain Knowledge in Neural Networks for Transprecision Computing, in: Machine Learning, Optimization, and Data Science. LOD 2020, Springer, «LECTURE NOTES IN COMPUTER SCIENCE», 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]Open Access
