Foto del docente

Federico Baldo

PhD Student

Department of Computer Science and Engineering

Research fellow

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Publications

Federico Baldo, Michele Iannello, Michele Lombardi, Michela Milano, Informed Deep Learning for Epidemics Forecasting, in: 11th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2022, 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]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

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]

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

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