National Program on Complex Data Structures-Workshop Organizers:

Tentative Schedule

Thursday October 28, 2004
8:30-9:00	REGISTRATION COFFEE AND CONTINENTAL BREAKFAST
9:00- 9:20	Opening Remarks
9:20-10:20	Helmut Kröger Learning in neural networks with small-world architecture.
10:20-10:45	COFFEE
10:45-12:15	Rare target problems Stan Young Linking and pattern matching in multiple large data two-way tables Mu Zhu An Adaptive Radial Basis Function Network Model for Statistical Detection" Grigoris Karakoulas ROC-based Learning for Imbalanced Class Problems
12:15-1:45	LUNCH
1:45-3:15	Unsupervised methods I Steven Wang Clustering Categorical Data Based on Distance Vectors Russel Steele, Algebraic Geometry and Model Selection for Naive Bayes Networks Xianping Liu Generation 5 Hybrid Clustering System and its Application
3:15-3:45	COFFEE/TEA BREAK
3:45-4:45	Feature extraction Roberto Aldave and Simon Gluzman Prediction of Real Variables with Non-Polynomial Approximants Wenxue Huang Dependence Degree and Feature Selection for Categorical Data
4:45-5:15	Daily discussant: William Welch, UBC
5:15-7:00	Reception hosted by
Friday October 29, 2004
8:30-9:00	COFFEE AND CONTINENTAL BREAKFAST
9:00-10:00	Jerome Friedman Importance Sampling: An Alternative View of Ensemble Learning* *Joint work with Bogdan Popescu
10:00-10:30	COFFEE
10:30-12:00	SAMSI data mining theme year speakers David Banks Scalability of Models in Data Mining Adele Cutler Random Forests: Proximity, Variable Importance, and Visualization* Joint work with Leo Breiman Merlise Clyde Bayesian Perspectives on Combining Models*
12:00-1:30	LUNCH
1:30-3:30	Supervised methods I Alex Depoutovitch The use of grid computing to speed up prediction Reuben Zamar Robust Methods and Data Mining Godfried Toussaint Proximity Graph Methods for Data Mining Alex Zolotovitski Automated Trade area analysis. Case study of G5 MWM software application
3:30-4:00	COFFEE/TEA BREAK
4:00-5:00	Ji Zhu and Saharon Rosset Is regularization: efficient and effective Piecewise linear SVM paths
5:00-5:30	Daily discussant: Hugh Chipman, Acadia University
5:30 -7:00	Reception hosted by the National Program on Complex Data Structures (cash bar)
Saturday October 30, 2004
8:30-9:00	COFFEE AND CONTINENTAL BREAKFAST
9:00-10:00	Yoshua Bengio Statistical Learning from High Dimensional and Complex Data: Not a Lost Cause
10:00-10:30	Coffee
10:30-12:00	Mining industrial process data Joaquin Ordieres Meré Data-Mining for industrial processes Theodora Kourti, Data Mining in Industry for Process and Product Improvement
12:00-1:30	LUNCH
1:30-3:30	Panel Discussion Tracey Jarosz, Loyalty group Jerome Friedman, Stanford University Theodora Kourti, McMaster University Rick Makos, Teradata Ivan Miletic, Dofasco Inc. Milorad Krneta, Generation 5 Stan Young, National Institute of Statistical Sciences, North Carolina
3:30-4:00	COFFEE/TEA BREAK
4:00-5:00	Djamel Zighed Constructing induction graphs

The National Program on
Complex Data Structures

Workshop on Data Mining Methodology and Applications
October 28-30, 2004
at The Fields Institute, Toronto
Supported by

Tentative Schedule

Thursday October 28, 2004

Friday October 29, 2004

Saturday October 30, 2004

The National Program on Complex Data Structures

Workshop on Data Mining Methodology and Applications October 28-30, 2004 at The Fields Institute, Toronto Supported by

Tentative Schedule

Thursday October 28, 2004

Friday October 29, 2004

Saturday October 30, 2004

The National Program on
Complex Data Structures

Workshop on Data Mining Methodology and Applications
October 28-30, 2004
at The Fields Institute, Toronto
Supported by