[Please excuse any duplicate copies of this announcement you may have received through other mailing lists. --- WHH] CALL FOR PARTICIPATION 15 Jul 2001 IJCAI-2001 Workshop on Wrappers for Performance Enhancement in Knowledge Discovery in Databases (KDD) [workshop code ML-5] http://www.kddresearch.org/KDD/Workshops/IJCAI-2001/ Saturday, 04 Aug 2001 Seattle, Washington, USA WORKSHOP DESCRIPTION The rapidly increasing volume of data collected for decision support applications in commercial, industrial, medical, and defense domains has made it a challenge to scale up knowledge discovery in databases (KDD), the machine learning and knowledge acquisition component of these applications. Many techniques currently applied to KDD admit enhancement through the WRAPPER approach, which uses empirical performance of inductive learning algorithms as feedback to optimize parameters of the learning system. Wrappers include algorithms for performance tuning, especially: optimization of learning system parameters (HYPERPARAMETERS) such as learning rates and model priors; control of solution size; and change of problem representation (or inductive bias optimization). Strategies for changing the representation of a machine learning problem include decomposition of learning tasks into more tractable subproblems; feature construction, or synthesis of more salient or useful input variables; and feature subset selection, also known as variable elimination (a form of relevance determination). This workshop will explore current issues concerning wrapper technologies for KDD applications. WORKSHOP AUDIENCE This workshop is intended for researchers in the area of machine learning, including practitioners of knowledge discovery in databases (KDD) and statistical and computational learning theorists. Intelligent systems researchers with an interest in high-performance computation and large-scale, real-world applications of data mining (e.g., inference and decision support) will also find this workshop of interest. INVITED TALKS "An Intelligent Assistant for the Knowledge Discovery Process" Abraham Bernstein and Foster Provost New York University "Bagging Considered Harmful" Charles Elkan University of California, San Diego ACCEPTED PAPERS "Unsupervised Model Selection via Evolutionary Local Search" Yongseok Kim, W. Nick Street, and Filippo Menczer "Parallel Online Continuous Arcing and a New Framework for Wrapping Parallel Ensembles" Jesse A. Reichler and Harlan D. Harris "Wrapper-Based Feature Selection for Multivariate Leaf Models" Edwin Pednault and Ramesh Natarajan "Wrappers for Automatic Parameter Tuning in Multi-Agent Optimization by Genetic Programming" William H. Hsu and Steven M. Gustafson "A Filter Implementation Using a Committee Machine of Wrappers" Cecil P. Schmidt CALL FOR PARTICIPATION Any interested attendees are welcome. To be invited to the workshop, send e-mail to the organizing committee at: [EMAIL PROTECTED] For the workshop agenda, electronic version of accepted papers, invited talks, and slide presentations, as well as up-to-date information on the committees and invited speakers, please visit the workshop web site: http://www.kddresearch.org/KDD/Workshops/IJCAI-2001/ IMPORTANT DATES Full Papers due: Monday, 02 April 2001 (extended deadline) Short Papers due: Friday, 06 April 2001 acceptance notification: Monday, 09 April 2001 camera-ready copy due: Friday, 20 April 2001 (extended deadline) workshop Saturday, 04 Aug 2001 ORGANIZING COMMITTEE William H. Hsu (primary contact) Kansas State University Hillol Kargupta University of Maryland Baltimore County Huan Liu Arizona State University Nick Street The University of Iowa ======================================================= William H. Hsu, Ph.D. Assistant Professor of CIS, Kansas State University Director, Lab for Knowledge Discovery in Databases [EMAIL PROTECTED], [EMAIL PROTECTED] http://www.kddresearch.org ICQ: 28651394 =======================================================
