Isolation Forest and recent development of isolation techniques for anomaly detection
Speaker: Associate Professor Kai-Ming Ting, Federation University, Australia
Date: Friday 13 June 2014
Time: 1.30pm to 3.00pm
Location: CB10.04.470
Seminar Chairman: Professor Longbing Cao, Director, AAi – Longbing.Cao@uts.edu.au
Abstract:
Isolation Forest, first introduced in 2008, is an anomaly detector with many unique features. First, it isolates anomalies, instead of profiling the norm which is the commonly used approach. Second, it does not use a distance measure. Third, it requires only a small training sample to produce a high-performing detector. As a result, Isolation Forest is one of the fastest anomaly detectors and one of the few that can easily scale up to big data.
This talk provides an introduction to Isolation Forest and describes the recent development of isolation techniques for anomaly detection.
Bio:
After receiving his PhD from the University of Sydney, Kai Ming Ting had worked at the University of Waikato, Deakin University and Monash University. He joins Federation University since 2014. He had previously held visiting positions at Osaka University, Nanjing University, and Chinese University of Hong Kong. His current research interests are in the areas of mass estimation, anomaly detection, ensemble approaches, data stream, data mining and machine learning in general. He has served as a program committee co-chair for the Twelfth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2008). He was a member of the program committee for a number of international conferences including ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, and International Conference on Machine Learning. He has received research funding from Australian Research Council, US Air Force of Scientific Research (AFOSR/AOARD), Toyota Info Technology Centre, and Australian Institute of Sports, totalling over one million since 2004. Awards received include the Runner-up Best Paper Award in 2008 IEEE ICDM, and the Best Paper Award in 2006 PAKDD.
Overview to AAI seminar series
The Advanced Analytics Seminar Series presents the latest theoretical advancement and empirical experience in a broad range of interdisciplinary and business-oriented analytics fields. It covers topics related to data mining, machine learning, statistics, bioinformatics, behavior informatics, marketing analytics and multimedia analytics. It also provides a platform for the showcase of commercial products in ubiquitous advanced analytics. Speakers are invited from both academia and industry. It opens regularly on a week day at UTS. You are warmly welcome to attend this seminar series. Inquiries go to the seminar coordinator Associate Professor Jinyan Li Jinyan.Li@uts.edu.au