3 papers
cs.LG2024
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD
Valentina Zaccaria, Chiara Masiero, David Dandolo +1
While Machine Learning has become crucial for Industry 4.0, its opaque nature hinders trust and impedes the transformation of valuable insights into actionable decision, a challeng…
cs.LG2024
AcME-AD: Accelerated Model Explanations for Anomaly Detection
Valentina Zaccaria, David Dandolo, Chiara Masiero +1
Pursuing fast and robust interpretability in Anomaly Detection is crucial, especially due to its significance in practical applications. Traditional Anomaly Detection methods excel…
stat.ML2023
Enhancing Interpretability and Generalizability in Extended Isolation Forests
Alessio Arcudi, Davide Frizzo, Chiara Masiero +1
Anomaly Detection (AD) focuses on identifying unusual behaviors in complex datasets. Machine Learning (ML) algorithms and Decision Support Systems (DSSs) provide effective solution…