Machine Learning (ML) achievements enabled automatic extraction of actionable information from data in a wide range of decision-making 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...
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2021 (v1)PublicationUploaded on: April 14, 2023
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2022 (v1)Publication
The increasing digitization and datification of all aspects of people's daily life, and the consequent growth in the use of personal data, are increasingly challenging the current development and adoption of Machine Learning (ML). First, the sheer complexity and amount of data available in these applications strongly demands for ML algorithms...
Uploaded on: April 14, 2023