Program

9:00-9:10

Opening by Associate Dean of Engineering
Dr. Peter Mascher

9:10-10:10

Invited

A Mathematical Programming Approach to Discovery in Graph Theory
P.Hansen

10:10-10:30

Break

10:30-11:00

1-1

Multiple Kernel Learning, Conic Duality, and the SMO Algorithm
G. Lanckriet  

11:00-11:30

1-2

I1 Regularization in Infinite Dimensional Predictor Spaces
S. Rossett

11:30-12:00

1-3

Maximum Margin Matrix Factorization
N. Srebro

12:00-14:00

Lunch

14:00-14:30

2A-1

Instance Selection and Metaheuristics
S. Olafsson

2B-1

The Neural Detection of Glycosylation Sites of the Epidermal Growth Factor
A. Darissi-Shaneh         

14:30-15:00

2A-2

Optimal Instance Selection for Smaller Decision Trees
S. Wu

2B-2

Linear Programming in Bounded Tree-width Markov Networks
P. Liang

15:00-15:30

2A-3

Optimal Instance Selection to Learning Best Scheduling Practices
X. Li

2B-3

Total Variation Based Medical Image Segmentation and Field Mapping
Z. Zheng

15:30-15:45

Break

Invited

Mathematical Programming and Statistical Models Based on Graphs
M. Wainwright

8:30-9:30

Invited

Data Mining Techniques  via Multiple Criteria Optimization Approaches
Y. Shi

9:30-9:45

Break

9:45-10:15

3-1

On the Minimum Volume Covering Ellipsoid of Ellipsoids
E. A. Yildirim           

10:15-10:45

3-2

k-Clustering and its applications
P. Kumar

10:45-11:15

3-3

INCAS: An incremental active set method for SVMs
K. Scheinberg

11:15-11:30

Break

11:30-12:30

Invited

A Review of Some Optimization in Machine Learning and Statistics
S. Wright

12:30-14:00

Lunch

14:00-14:30

4-1

Machine learning and optimization for gene regulation
C. Leslie

14:30-15:00

4-2

Integrating heterogeneous data using semi-definite programming
G. Lanckriet   

15:00-15:30

4-3

Applications of Gibbs sampling in bioinformatics
Q. Sheng

15:30-15:45

Break

15:45-16:45

Invited

Optimization Challenges in Capacity Control
K. Bennett

16:45-17:00

Break

17:00-17:30

5-1

Factor Analysis Model for Functional Genomics
R. Shioda

17:30-18:00

5-2

Inferring regulatory modules  from heterogeneous data sources: a data mining approach
T. De Bie

18:00-18:30

5-3

Pattern Analysis Challenges in Bioinformatics
N. Cristianini

8:30-9:30

Invited

Unsupervised and Supervised Classification via Nonsmooth Optimization
A. Rubinov

9:30-9:45

Break

9:45-10:15

6A-1

Solving a mixed-integer programming formulation of a classification model
P. Brooks

6B-1

A multi-group multiple criteria mathematical
programming approach in data mining
Y. Peng

10:15-10:45

6A-2

A Nonsmooth Newton Method for Multi-class Classification
P. Zhong

6B-2

On approximate Balanced Bi-clustering
Y. Wei

10:45-11:15

6A-3

Linear and nonlinear discrimination via homogeneous analytic center cutting plane method
N. Sawhney

11:15-11:30

Break

Discrete Optimization Problems in the Logical Analysis of Data
P. Hammer

12:30-14:00

Lunch

14:00-14:30

7-1

Zero Norm Least Squares Proximal Regression  
S. Shah

14:30-15:00

7-2

Potential Proximal Support Vector Machines for Data Classification
R. Khemchandan

15:00-15:30

7-3

A Fast and Efficient Learning Algorithm for  Support Vector Regression Problems
R. Debnath

15:30-16:00

Break

16:00-17:00

Invited

Latent Variable Methods for Process Analysis, Monitoring and Design
J. MacGregor

17:30

Dinner Cruise aboard the Hamilton Habour Queen

9:00-10:00

Invited

Identifying and Solving Important/Complex Problems
S. Young

10:00-10:15

Break

10:15-10:45

8A-1

Comparison of data mining algorithms in the diagnosis of breast cancer
J.F. Arocha

8B-1

The prediction-correction approach to nonlinear complementarity problems
X. Yuan

10:45-11:15

8A-2

Data Mining the interRAI Minimum Mental  Health Data Set
K. Ponnambalam         

8B-2

Random CSP: Definition, Creation, and Algorithms Comparison (SLIDES)(PAPER)
T. Lin

Parallel Evolution Strategy for Protein Threading
R. Islam

K-means Clustering, Principal Component Analysis and 0-1 SDP
J. Peng

11:45-12:00

Closing Remarks