Foto del docente

Michele Lombardi

Professore associato

Dipartimento di Informatica - Scienza e Ingegneria

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

Pubblicazioni

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

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

Salvagnin, Domenico; Lombardi, Michele, Introduction to the CPAIOR 2017 fast track issue, «CONSTRAINTS», 2017, 22, pp. 491 - 492 [replica/breve intervento]

DE FILIPPO, Allegra; Lombardi, Michele; Milano, Michela; Borghetti, Alberto, Robust Optimization for Virtual Power Plants, in: Proceedings of AI*IA 2017, 2017, 10640, pp. 17 - 30 (atti di: AI*IA 2017 - 16th International Conference of the Italian Association for Artificial Intelligence, Bari, 14-17 Nov 2017) [Contributo in Atti di convegno]

DE FILIPPO, Allegra; Lombardi, Michele; Milano, Michela, User-aware electricity price optimization for the competitive market, «ENERGIES», 2017, 10, pp. 1 - 23 [articolo]Open Access

Bridi, Thomas; Bartolini, Andrea; Lombardi, Michele; Milano, Michela; Benini, Luca, A Constraint Programming Scheduler for Heterogeneous High-Performance Computing Machines, «IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS», 2016, 27, pp. 2781 - 2794 [articolo]Open Access

Lombardi, Michele; Gualandi, Stefano, A lagrangian propagator for artificial neural networks in constraint programming, «CONSTRAINTS», 2016, 21, pp. 435 - 462 [articolo]

Bridi, Thomas; Lombardi, Michele; Bartolini, Andrea; Benini, Luca; Milano, Michela, DARDIS: Distributed and randomized DIspatching and scheduling, in: Frontiers in Artificial Intelligence and Applications, ;Nieuwe Hemweg 6B, IOS Press, 2016, 285, pp. 1598 - 1599 (atti di: 22nd European Conference on Artificial Intelligence, ECAI 2016, nld, 2016) [Contributo in Atti di convegno]

Bridi, Thomas; Lombardi, Michele; Bartolini, Andrea; Benini, Luca; Milano, Michela, DARDIS: Distributed and randomized dispatching and scheduling, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, 2016, 10037, pp. 493 - 507 (atti di: 15th International Conference on Italian Association for Artificial Intelligence, AIIA 2016, ita, 2016) [Contributo in Atti di convegno]

De Filippo, Allegra; Lombardi, Michele; Milano, Michela, Non-linear optimization of business models in the electricity market, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, 2016, 9676, pp. 81 - 97 (atti di: 13th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, CPAIOR 2016, can, 2016) [Contributo in Atti di convegno]

Borghesi, Andrea; Bartolini, Andrea; Lombardi, Michele; Milano, Michela; Benini, Luca, Predictive modeling for job power consumption in HPC systems, in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Verlag, 2016, 9697, pp. 181 - 199 (atti di: 31st International Conference on High Performance Computing, ISC High Performance 2016, deu, 2016) [Contributo in Atti di convegno]

Ultimi avvisi

Al momento non sono presenti avvisi.