Organizers:
George Cybenko (Dartmouth College) and Avner Friedman (IMA)

Data Mining is becoming increasingly important in industry where one would like to make decisions such as to mail/not mail a catalog, how to maximize customer's satisfaction, what message to send on the networks to specific groups of callers, etc. The modeling issues combine methods of pattern recognition, computer science and statistics.

Given database, one would like to design partitions that give accurate description; feature analysis is required to determine where are the information bearing variables; non-parametric techniques and neural networks may possibly be used to achieve very high insight. The goal of data mining is to achieve predictive modeling, based on accuracy and insight.

The period of concentration brought together researchers from industry and university in order to (i) identify the current and future problem areas, (ii) review the mathematical and statistical approaches presently being used, and (iii) discuss and determine which research directions would be most promising.

Workshop Schedule

Click on the titles to find abstracts and/or links to presentation materials

SCHEDULE for MONDAY, NOVEMBER 18
A.Friedman, R.Gulliver, G. Cybenko	Welcome and Orientation
George Cybenko, Darmouth College	Introductory Remarks
Chid Apte, IBM Watson Research Labs	Data Mining and its Industrial Applications
Daryl Pregibon, AT & T Research
Abhiram Ranade, Indian Institute of Technology	Computer Science Colloquium: Bandwidth-efficient parallel computation
SCHEDULE for TUESDAY, NOVEMBER 19
Mark Embrechts, Rensselaer Polytechnical Inst.	Neural networks for data mining and knowledge discovery
Bala Iyer, IBM Santa Teresa Labs	Money Mining
Vipin Kumar, University of Minnesota	Parallel Data Mining Algorithms
SCHEDULE for WEDNESDAY, NOVEMBER 20
Simon Kasif, Johns Hopkins University	Towards High-Performance Intelligent Systems for Data Modelling
Gregory Piatetsky-Shapiro, GTE Labs, Waltham	Developing Industrial Data Mining and Knowledge Discovery Applications: an Overview of Issues
Ramasamy Uthurusamy, General Motors R & D Center	Architectures for Data Mining Over Enterprise Intranets

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1996-1997 Mathematics in High Performance Computing