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Rare Event Detection
Description
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Previous Workshops
...The focus of this workshop
will be on machine learning algorithms for surveillance and event detection
in complex forms of data, novel application areas for event detection, and
new directions for this type of research.
This workshop aims to explore
research efforts on data mining, machine learning, and related techniques
that address the problem of detecting anomalies (irregularities that cannot
be explained by simple domain models and knowledge) in data. The workshop
will also attempt to study the common tasks that need to be addressed in
practical applications that require anomaly detection tools and algorithms,
such as data collection, sampling, and pre-processing.
Researchers in This
Field
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Naoki Abe, IBM, T.J. Watson
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Mihael Ankerst, Allianz
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Stephen Bay,
PricewaterhouseCoopers
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Carla Brodley, Tufts
University
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Philip Chan, Florida
Institute of Technology
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Vince Clark, University of
New Mexico
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Diane Cook, University of
Texas, Arlington
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Chris Drummond, The National
Research Council of Canada
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Wei Fan, IBM, T.J. Watson
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Eamonn Keogh, University of
California, Riverside
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Adam Kowalczyk, National ICT
Australia
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Terran Lane, University of
New Mexico
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Alekasnder Lazarevic,
University of Minnesota
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Wenke Lee, Georgia Tech
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Dragos Margineantu, Boeing,
Mathematics and Computing Technology
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Raju Mattikalli, The Boeing
Company
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Ion Muslea,Language Weaver,
Inc.
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John McGraw, University of
New Mexico
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Raymond Ng, University of
British Columbia
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Mark Schwabacher, NASA, Ames
Research Center
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Galit Shmueli, University of
Maryland, College Park
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Salvatore Stolfo, Columbia
University
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Weng-Keen Wong, University of
Pittsburgh
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Bianca Zadrozny, IBM, T.J.
Watson
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... ...
Last Modified: 2007-04-05 by Xu-Ying Liu
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Machine Learning Topics
Cost-Sensitive Learning
Imbalance Problem Rare Event Detection
ROC Analysis |