Advisor
F. Angiulli
Co-advisor
F. Fassetti
Research Topic
Meta and Multi-Task learning for the Anomaly Detection Task
Research Abstract
Anomaly detection is a crucial task in the field of data analysis and machine learning, aimed at identifying patterns, events or observations that deviate significantly from the expected behavior within a given data set. Also known as anomaly detection, this task plays a key role in various fields such as cybersecurity, finance, healthcare and industrial monitoring.
This PhD research project aims to study and implement new techniques for the Anomaly Detection Task using techniques based on the Multi-Task and Meta Learning paradigms.