2008 Summer School

2008 SUMMER SCHOOL

on Advances in Data Mining May 5-8, 2008

Objectives
This summer school on Advances in Data Mining is primarily intended for graduate students and researchers wishing to enlarge their knowledge in data mining, its applications and its recent developments. Eight tutorial lectures of three hours each will be given by seven experts in data mining.

Venue

HEC Montréal (Building no. 35 on the University of Montreal campus map)
3000, chemin de la Côte-Sainte-Catherine
Montréal (Québec) H3T 2A7

Scientific Program

All lectures will be held in room Van Houtte on the first floor in the green section. Email facilities: Hewitt Équipement Limitée. Coffee breaks are at 10:15 to 10:30 and 15:15 to 15:30.

Monday, May 5, 2008
8:15 – 9:00	Registration (in front of room Van Houtte)
9:00 – 12:00	Text Mining Gilles Caporossi, GERAD & HEC Montréal, Montréal, Canada Some Recent Developments in Tree Based Methods Denis Larocque, GERAD & HEC Montréal, Montréal, Canada
12:00 – 14:00	Lunch (Salon Deloitte, 4^th floor)
14:00 – 17:00	A Survey of Statistical Learning David Banks, Duke University, North Carolina, USA
17:00 – 20:00	Cocktail party (Salon Deloitte, 4^th floor)
Tuesday, May 6, 2008
9:00 – 12:00	A Survey of Statistical Learning David Banks, Duke University, North Carolina, USA
12:00 – 14:00	Lunch (Teleglobe, Garden Level)
14:00 – 17:00	Partially Defined Boolean Functions and Logical Analysis of Data Endre Boros, Rutgers University, New Jersey, USA
Wednesday, May 7, 2008
9:00 – 12:00	Clustering Algorithms Pierre Hansen, GERAD & HEC Montréal, Montréal, Canada
12:00 – 14:00	Lunch (Salon Deloitte, 4^th floor)
14:00 – 17:00	Partially Defined Boolean Functions and Logical Analysis of Data Endre Boros, Rutgers University, New Jersey, USA
Thursday, May 8, 2008
9:00 – 12:00	On the Relevance of Neural Networks for Data Mining: How They Work, Why They Matter, and the Promises of Current Research Pascal Vincent, Université de Montréal, Montréal, Canada
12:00 – 14:00	Lunch (restaurant)
14:00 – 17:00	Data mining in a cubicle: what happens after graduation day? Michel Girard, Aéroplan, Montréal, Canada

The topics covered will be:
Machine Learning, Clustering Algorithms, Neural Networks, Logical Analysis of Data (LAD), Trees, Text Mining and the use of Data Mining in Business.

Registrations Fees (in Canadian dollars)*

Online registration.

	Before April 15	After April 15
Students	$ 300	$ 400
Others	$ 600	$ 700

Fees include one-week registration, a copy of school textbook, 8 coffee breaks, 4 lunches and one cocktail.

* There is a limit of 50 participants.

Accommodation

Accommodation list.

Contact

For additional information you can reach Ms Carole Dufour at GERAD, by phone at (1) 514-340-6053 extension 6043, by fax at (1) 514-340-5269,
or by email at ecole2008@gerad.ca.