CALL FOR PAPERS ICML-KDD'2003 Workshop: Learning from Imbalanced Data Sets II Thursday, August 21, 2003 Washington, DC ------------------------------------------------------------------------ Organizers: ----------- Nitesh Chawla, Business Analytic Solutions, CIBC (chawla@csee.usf.edu) Nathalie Japkowicz, University of Ottawa (nat@site.uottawa.ca) Aleksander Kolcz, America Online, Inc. (ark@pikespeak.uccs.edu) ------------------------------------------------------------------------ Workshop Page: -------------- http://www.site.uottawa.ca/~nat/Workshop2003/workshop2003.html ------------------------------------------------------------------------ Workshop Description: --------------------- Overview: Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced learning data, where at least one class is under-represented relative to others. Examples include (but are not limited to): fraud/intrusion detection, risk management, medical diagnosis/monitoring, bioinformatics, text categorization and personalization of information. The problem of imbalanced data is often associated with asymmetric costs of misclassifying elements of different classes. Additionally the distribution of the test data may differ from that of the learning sample and the true misclassification costs may be unknown at learning time. The AAAI-2000 Workshop on "Learning from Imbalanced Data Sets" provided the first venue where this important problem was explicitly addressed and has been received with much interest. The related ICML-2000 Workshop on "Cost-Sensitive Learning" provided another venue for addressing the problem of asymmetric costs of different classes and features. Although much awareness of the issues related to data imbalance has been raised, many of the key problems still remain open and are in fact encountered more often, especially when applied to massive datasets. We believe that it would be of value to the machine learning community to not only examine the progress achieved in this area over the last three years but also discuss the current school of thought on research in learning from imbalanced datasets. Based on our understanding of class imbalance problem, the following topics of discussion are proposed (but not limited to): * sampling (under-, over-, progressive, active) * post-processing of learned models * accounting for class imbalance via inductive bias * one-sided learning * handling uncertainty of target distribution and misclassification costs * handling varying amounts (class dependent) of label noise Proposed Format: The workshop will open with an invited talk by Foster Provost that will introduce and overview the topic. Presentations will then be organized into several sessions corresponding roughly to the to the categories identified above. The workshop will conclude with a discussion during which a distinguished guest will comment on the presentations of the day, and open the floor for general discussion. Proposed Length: One Day during which each panel will be allocated 1 to 2 hours, depending on the number of contributions and the expected length of the discussion session. Workshop Notes: The accepted papers will be available electronically from the workhop website, and also as printed workshop notes to the attendees. Submissions: Authors are invited to submit papers on the topics outlined above or on other related issues. Submissions should not exceed 8 pages, and should be in line with the ICML style sheet. Electronic submissions, in PDF format, are prefered and should be sent to: Nitesh Chawla at chawla@morden.csee.usf.edu If electronic submissions are inconvenient, please send four hard copies of your submission to: Dr. Nitesh Chawla Business Analytic Solutions, TBRM, CIBC, BCE Place, 161 Bay Street, 11th Floor, Toronto, Ontario M5J 2S8, Canada ------------------------------------------------------------------------ Timetable: ---------- * Submission deadline: May 1, 2003 * Notification date: May 25, 2003 * Final date for camera-ready copies to organizers: June 8, 2003 ------------------------------------------------------------------------ Invited Speakers: ----------------- Foster Provost New York University, USA Others To Be Announced ------------------------------------------------------------------------ Program Committee: ------------------ Kevin Bowyer University of Notre Dame, USA Chris Drummond National Research Council, Canada Charles Elkan University of California San Diego, USA Marko Grobelnik Jozef Stefan Institute, Slovenia Larry Hall University of South Florida, USA Robert Holte University of Alberta, Canada W.Philip Kegelmeyer Sandia National Labs, USA Miroslav Kubat University of Miami, USA Aleksandar Lazarevic University of Minnesotta, USA Charles Ling University of Western Ontario, Canada Dragos Margineantu Boeing Corporation, USA Foster Provost New York University, USA Gary Weiss AT&T Labs, USA