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 [Scientific article]Open Access
Morais A.; Barbosa R.; Lourenco N.; Cerveira F.; Lombardi M.; Madeira H., Strategies for Improving the Error Robustness of Convolutional Neural Networks, in: Proceedings of QRS 2022, 2022, 2022-December, pp. 874 - 883 (atti di: QRS 2022, Guangzhou, China, December 5-9, 2022) [Contribution to conference proceedings]
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: 11th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2022, IOS Press BV, 2022, 351, pp. 114 - 127 (atti di: PAIS 2022, Vienna, Austria, 25 July 2022) [Contribution to conference proceedings]Open Access
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: 2022 IEEE International Smart Cities Conference (ISC2), New York, IEEE, 2022, pp. 1 - 7 (atti di: ISC 2022, Pafos, Cyprus, September 26-29, 2022) [Contribution to conference proceedings]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, 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) [Contribution to conference proceedings]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) [Contribution to conference proceedings]Open Access
Helmberg H.; Lacalandra F.; Schmidt M.; Henriques C.; De Filippo A.; Lombardi M.; Milano M.; Ezran P.; Haddad Y.; Diekerhof M.; Madani M., Finance, Regulations, Politics and Market Design, in: AIRO Springer Series, Berlin, Springer Nature, 2021, pp. 59 - 75 (AIRO SPRINGER SERIES) [Chapter or essay]
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, 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) [Contribution to conference proceedings]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 [Scientific article]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, 2021, 12461, pp. 118 - 135 (atti di: European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, Ghent, Belgium, 2020) [Contribution to conference proceedings]
Diekerhof M.; Monti A.; Lebedeva E.; Tkaczyk A.H.; Yuksel-Ergun I.; Zittel J.; Escudero L.F.; Soroudi A.; Helmberg C.; Kanovic Z.; Petkovic M.; Lacalandra F.; Frangioni A.; Lee J.; De Filippo A.; Lombardi M.; Milano M.; Ezran P.; Haddad Y., Production and Demand Management, in: AIRO Springer Series, Berlin, Springer Nature, 2021, pp. 3 - 25 (AIRO SPRINGER SERIES) [Chapter or essay]
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, 2021, 35, pp. 3742 - 3749 (atti di: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual event, 2-9 February) [Contribution to conference proceedings]
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) [Contribution to conference proceedings]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, 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) [Contribution to conference proceedings]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, 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) [Contribution to conference proceedings]Open Access
