[Please excuse any duplicate copies of this announcement you
may have received through other mailing lists. --- WHH]
FINAL CALL FOR PARTICIPATION
28 Feb 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.
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
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
Research Scientist, Automated Learning Group, NCSA
bhsu@cis.ksu.edu, bhsu@ncsa.uiuc.edu
http://www.cis.ksu.edu/~bhsu ICQ: 28651394
-----------------------------------------------------------------------------
This archive was generated by hypermail 2b29 : Thu Mar 01 2001 - 12:32:57 PST