Non-Parametric Stochastic Autoencoder Model for Anomaly Detection

• Main Authors: Alampay, Raphael B, Abu, Patricia Angela R
• Format: text
• Published: Archīum Ateneo 2022
• Subjects: Neural networks; autoencoders; machine learning; anomaly detection; semi-supervised learning; Computer Sciences; Databases and Information Systems; Electrical and Computer Engineering; Physical Sciences and Mathematics
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/342; https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1342&context=discs-faculty-pubs
• Institution: Ateneo De Manila University

Anomaly detection is a widely studied field in computer science with applications ranging from intrusion detection, fraud detection, medical diagnosis and quality assurance in manufacturing. The underlying premise is that an anomaly is an observation that does not conform to what is considered to be...