Foto del docente

Michele Lombardi

Senior assistant professor (fixed-term)

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Publications

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

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, 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) [Contribution to conference proceedings]

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 [Scientific article]

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) [Contribution to conference proceedings]

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) [Contribution to conference proceedings]

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, 2019, 11802, pp. 108 - 125 (atti di: 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, usa, 2019) [Contribution to conference proceedings]

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, «IJCAI», 2018, 2018-, pp. 5472 - 5478 (atti di: 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, swe, 2018) [Contribution to conference proceedings]

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) [Contribution to conference proceedings]

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 [Scientific article]

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, «IJCAI», 2018, 2018-, pp. 1270 - 1276 (atti di: 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, swe, 2018) [Contribution to conference proceedings]

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, 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) [Contribution to conference proceedings]

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) [Contribution to conference proceedings]

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 [Scientific article]

Lombardi, Michele; Milano, Michela; Bartolini, Andrea, Empirical decision model learning, «ARTIFICIAL INTELLIGENCE», 2017, 244, pp. 343 - 367 [Scientific article]

Salvagnin, Domenico; Lombardi, Michele, Introduction to the CPAIOR 2017 fast track issue, «CONSTRAINTS», 2017, 22, pp. 491 - 492 [Comment or similar]

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