KDD 2020: Robust Deep Learning Methods for Anomaly Detection

KDD 2020: Robust Deep Learning Methods for Anomaly Detection

Explore robust deep learning methods for anomaly detection in this 24-minute conference talk from KDD 2020. Delve into various techniques, including video surveillance, spectral methods, PCA, and auto-encoders. Learn about matrix factorization approaches and robust convolutional auto-encoders (RCAE). Compare conventional and deep learning-based anomaly detection methods through experiments on diverse datasets. Discover the performance of non-inductive anomaly detection and image de-noising capabilities of RCAE versus RPCA. Gain insights from speakers Raghavendra Chalapathy, Khoa Nguyen, and Sanjay Chawla as they present their findings and conclusions on advanced anomaly detection techniques.