Machine Learning (ML) achievements enabled automatic extraction of actionable information from data in a wide range of decisionmaking scenarios. This demands for improving both ML technical aspects (e.g., design and automation) and human-related metrics (e.g., fairness, robustness, privacy, and explainability), with performance guarantees at both levels. The aforementioned scenario posed three main challenges: (i) Learning from Complex Data (i.e., sequence, tree, and graph data), (ii) Learning Trustworthily, and (iii) Learning Automatically with Guarantees. The focus of this special session is on addressing one or more of these challenges with the final goal of Learning Trustworthily, Automatically, and with Guarantees from Complex Data.

Oneto, L., Navarin, N., Biggio, B., Errica, F., Micheli, A., Scarselli, F., et al. (2021). Complex Data: Learning Trustworthily, Automatically, and with Guarantees. In ESANN 2021 Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publ..

Complex Data: Learning Trustworthily, Automatically, and with Guarantees

Franco Scarselli;Monica Bianchini;
2021-01-01

Abstract

Machine Learning (ML) achievements enabled automatic extraction of actionable information from data in a wide range of decisionmaking scenarios. This demands for improving both ML technical aspects (e.g., design and automation) and human-related metrics (e.g., fairness, robustness, privacy, and explainability), with performance guarantees at both levels. The aforementioned scenario posed three main challenges: (i) Learning from Complex Data (i.e., sequence, tree, and graph data), (ii) Learning Trustworthily, and (iii) Learning Automatically with Guarantees. The focus of this special session is on addressing one or more of these challenges with the final goal of Learning Trustworthily, Automatically, and with Guarantees from Complex Data.
978287587082-7
Oneto, L., Navarin, N., Biggio, B., Errica, F., Micheli, A., Scarselli, F., et al. (2021). Complex Data: Learning Trustworthily, Automatically, and with Guarantees. In ESANN 2021 Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publ..
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1166479