FIRST CALL FOR PARTICIPATION 30 Dec 2000 2001 International Joint Conference on Artificial Intelligence (IJCAI-01) 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, 4 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. =20 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. CALL FOR PAPERS We encourage submissions containing original theoretical and applied concepts in KDD. Experimental results are also encouraged, especially on fielded applications, even if they are only preliminary. We therefore invite two categories of paper submissions: - research papers - short summaries (including position papers) For the workshop agenda, submission procedure, and up-to-date information on the review committee and invited speakers, please visit the workshop web site: www.kddresearch.org/KDD/Workshops/IJCAI-2001/ IMPORTANT DATES Full Papers due: Friday, 02 Mar 2001 Short Papers due: Friday, 16 Mar 2001 acceptance notification: Friday, 30 Mar 2001 camera-ready copy due: Friday, 13 Mar 2001 workshop Saturday, 04 Aug 2001 ORGANIZING COMMITTEE William H. Hsu (primary contact) Kansas State University Hillol Kargupta Washington State University Huan Liu Arizona State University Nick Street The University of Iowa ----------------------------------------------------------------------------- William H. Hsu, Ph.D. Assistant Professor of CIS, Kansas State University Research Scientist, Automated Learning Group, NCSA [EMAIL PROTECTED], [EMAIL PROTECTED] http://www.cis.ksu.edu/~bhsu ICQ: 28651394
