Faculty of Informatics and Statistics, Department of Information and Knowledge Engineering (DIKE)

Date and time: March 1 2018 (16:00 – 17:30).

Room: 473 NB


Anomaly detection


  • Luboš Popelínský, NLP Lab, Fakulta informatiky, MUNI Brno

Nowadays, anomaly (outlier, rare event) detection is a very active research and application area. After a short introduction to anomaly detection and its succesful applications, I bring an overview of three settings - supervised, semi-supervised and unsupervised, and introduce basic methods for detecting anomalies. Then I will focus on current research directions, namely on evaluation of anomaly detection methods, on anomaly explanation, class-based outliers and outliers in text.

Downloads: slides 1  slides 2 

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