De Filippo, Allegra; Giuliani, Luca; Mancini, Eleonora; Borghesi, Andrea; Mello, Paola; Milano, Michela, Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations, in: Thirty-Second International Joint Conference on Artificial Intelligence, 2023, pp. 5806 - 5814 (atti di: Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23), Macao, 19-25 agosto 2023) [Contribution to conference proceedings]
Luca Giuliani, Allegra De Filippo, Andrea Borghesi, Paola Mello, Michela Milano, A Multi-modal Perspective for the Artistic Evaluation of Robotic Dance Performances, in: CREAI 2022, Workshop on Artificial Intelligence and Creativity, 2022, pp. 84 - 93 (atti di: Workshop on Artificial Intelligence and Creativity co-located with 21th International Conference of the Italian Association for Artificial Intelligence, Udine, 28 novembre 2022 - 3 dicembre 2022) [Contribution to conference proceedings]
Borghesi A.; Molan M.; Milano M.; Bartolini A., Anomaly Detection and Anticipation in High Performance Computing Systems, «IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS», 2022, 33, pp. 739 - 750 [Scientific article]Open Access
De Filippo A.; Mello P.; Milano M., Do You Like Dancing Robots? AI Can Tell You Why, in: PAIS 2022, 2022, 351, pp. 45 - 58 (atti di: 11th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2022), Vienna, 25/07/2022) [Contribution to conference proceedings]Open Access
De Filippo, A; Borghesi, A; Boscarino, A; Milano, M, HADA: An automated tool for hardware dimensioning of AI applications, «KNOWLEDGE-BASED SYSTEMS», 2022, 251, Article number: 109199 , pp. 1 - 18 [Scientific article]
Federico Baldo, Michele Iannello, Michele Lombardi, Michela Milano, Informed Deep Learning for Epidemics Forecasting, in: Frontiers in Artificial Intelligence and Applications, IOS Press BV, 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) [Contribution to conference proceedings]
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
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
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
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, 2020, 12565, pp. 587 - 600 (atti di: The Sixth International Conference on Machine Learning, Optimization, and Data Science, Siena, July 19-23, 2020) [Contribution to conference proceedings]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, 2020, 2659, pp. 44 - 51 (atti di: 1st International Workshop on New Foundations for Human-Centered AI, NeHuAI 2020, esp, 2020) [Contribution to conference proceedings]Open Access
