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
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]
De Filippo, Allegra; Lombardi, Michele; Milano, Michela, How to Tame Your Anticipatory Algorithm, in: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, pp. 1071 - 1077 (atti di: International Joint Conference on Artificial Intelligence, Macao, Agosto 2019) [Contributo in Atti di convegno]
Chisca D.S.; Lombardi M.; Milano M.; O'Sullivan B., Logic-Based Benders Decomposition for Super Solutions: An Application to the Kidney Exchange Problem, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2019, 11802, pp. 108 - 125 (atti di: 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, usa, 2019) [Contributo in Atti di convegno]
Lombardi, Michele; Milano, Michela, Boosting combinatorial problem modeling with machine learning, in: IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2018, 2018-, pp. 5472 - 5478 (atti di: 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, swe, 2018) [Contributo in Atti di convegno]
Chisca, Danuta; Lombardi, Michele; Milano, Michela; O'Sullivan, Barry, From Offline to Online Kidney Exchange Optimization, in: IEEE 30th International Conference on Tools with Artificial Intelligence, ICTAI 2018, 5-7 November 2018, Volos, Greece, IEEE, 2018, pp. 587 - 591 (atti di: IEEE 30th International Conference on Tools with Artificial Intelligence, ICTAI 2018, Volos, Greece, 5-7 November 2018) [Contributo in Atti di convegno]
Cauwelaert, Sascha Van*; Lombardi, Michele; Schaus, Pierre, How efficient is a global constraint in practice?: A fair experimental framework, «CONSTRAINTS», 2018, 23, pp. 87 - 122 [articolo]
De Filippo, Allegra; Lombardi, Michele; Milano, Michela, Methods for off-line/on-line optimization under uncertainty, in: IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2018, 2018-, pp. 1270 - 1276 (atti di: 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, swe, 2018) [Contributo in Atti di convegno]
Galassi Andrea,
Lombardi Michele,
Mello Paola,
Milano Michela, Model Agnostic Solution of CSPs via Deep Learning: A Preliminary Study, in: Willem-Jan van Hoeve, Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Springer International Publishing, «LECTURE NOTES IN COMPUTER SCIENCE», 2018, pp. 254 - 262 (atti di: 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Delft, The Netherlands, June 26–29, 2018) [Contributo in Atti di convegno]
De Filippo, Allegra; Lombardi, Michele; Milano, Michela, Off-Line and On-Line Optimization Under Uncertainty: A Case Study on Energy Management, in: Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2018, 10848, pp. 100 - 116 (atti di: CPAIOR 2018, Delft, 26-29 giugno 2018) [Contributo in Atti di convegno]
Borghesi, Andrea; Bartolini, Andrea; Lombardi, Michele; Milano, Michela; Benini, Luca, Scheduling-based power capping in high performance computing systems, «SUSTAINABLE COMPUTING», 2018, 19, pp. 1 - 13 [articolo]Open Access
