DIMACS Workshop on Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications

May 14 - 16, 2003
DIMACS Center, Rutgers University, Piscataway, NJ

Organizers:

Regina Liu, Rutgers University, rliu@stat.rutgers.edu

Robert Serfling, University of Texas at Dallas, serfling@utdallas.edu

Diane Souvaine, Tufts University, dls@eecs.tufts.edu

Yehuda Vardi, Rutgers University, vardi@stat.rutgers.edu

This material is based upon work supported by the National Science Foundation under Grant No. 0205136.

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

Preliminary Program:

Wednesday, May 14, 2003

 8:00 -  9:00   Breakfast and registration

 9:00  - 9:10   Opening remarks
                Melvin Janowitz, Associate Director of DIMACS

 9:10 -  9:20   Yehuda Vardi
                Department of Statistics, Rutgers University

 9:20 -  9:40   Marianthi Markatou
                Program Director, NSF Statistics Program

       Chair:   Arthur Cohen

 9:40 - 10:40   An Overview on Depth Functions in
                Nonparametric Multivariate Analysis
		Robert Serfling, University of Texas at Dallas             

10:40 - 11:00	Short Break

       Chair:   Diane Souvaine   

11:00 - 12:00   Depth and Arrangements
                David Eppstein, University of California, Irvine               

12:00 -  1:20   Lunch

       Chair:   Xuming He

 1:20 -  2:00   Data Analysis by Zonoid Depth 
	        Karl Mosler, Universitat zu Koln, Germany

 2:00 -  2:40	Data Depth in Multivariate Analysis:
                Dependence, Discrimination and Clustering
	        Mario Romanazzi, "Ca' Foscari University of Venice, Italy

 2:40 -  3:00   Fast Algorithms for Frames and Point Depth
                in Polyhedral Hulls
		Jose Dula, University of Mississippi and the U.S. Census Bureau

 3:00 - 3:20    A Note on Simplicial Depth
                Michael Burr,  Tufts University

 3:20 -  3:40   Break

       Chair:   David Madigan

 3:40 -  4:20   Maximal Depth Estimators of Regression Quantiles
                for Censored Data
		Steve Portnoy, University of Illinois

 4:20 -  5:00   Data Depth and Mixture Models
		Ryan Elmore, Thomas Hettmansperger*, Fengjuan Xuan
		Penn State University

 5:00 -  5:40   Comparing Multivariate Scale Using Data Depth: Testing
                for Expansion or Contraction
 		Kesar Singh, Rutgers University

 5:40 -  6:00  	A Test for Equal Variances Using Data Depth
 		Karen McGaughey, Kansas State University

 6:00 -  7:00   RECEPTION, Wine and Cheese, DIMACS Lounge 


Thursday, May 15, 2003


 8:30 -  9:00   Breakfast and registration

       Chair:   Marshall Bern

 9:00 -  9:40   Real-time Computation of Data Depth Using
                the Graphics Pipeline
  		Suresh Venkatasubramanian, AT&T Labs- Research
 
 9:40 - 10:20   Computing the Center of Area of a Convex Polygon
		Pat Morin, Carleton University, Canada

10:20 - 10:40   Distance Problems on points and lines
		Ovidiu Daescu, Ningfang Mi, University of Texas at Dallas

10:40 - 11:00   Short Break

       Chair:   Cun-Hui Zhang

11:00 - 11:40   Computation of Projection Depth and Related
                Estimators
                Yijun Zuo, Michigan State University

11:40 - 12:20   On some Probabilistic Algoritms for Computing
                Tukey's Half Space Depth
		Biman Chakraborty*, Probal Chaudhuri

12:20 -  1:50   Lunch
       
       Chair:   Evarist Gine

 1:50 -  2:30   On data based distances between
		data vectors and between hyperplanes
		Hannu Oja, University of Jyvaskyla, Finland

 2:30 -  3:10   Beyond Multivariate Location: Halfspace Depth in Various
		Models of Data Analysis
		Ivan Mizera, University of Alberta

 3:10 -  3:50   Yehuda Vardi
                Deep Talk

 3:50 -  4:20   Break

       Chair:   David Tyler

 4:20 -  4:40   A definition of depth for functional observations
		Sara López-Pintado, Juan Romo*
		Universidad Carlos III de  Madrid, Spain 

 4:40 -  5:00	A Depth_Based Kurtosis Functional  
 		Jin Wang, University of Texas at Dallas

 5:00 -  5:20	A Computational Tool for Depth-Based Statistical Analysis
                Eynat Rafalin, Tufts University 

 5:20 -  6:00   Tukey depth-based trimmed means
                Jean-Claude Masse, Universite Laval, Quebec, Canada

 6:20           DINNER, Faculty Dining Hall


Friday, May 16, 2003

 8:30 -  9:00   Breakfast and registration

       Chair:   William Steiger

 9:00 -  9:40   Clustering and Cluster validation via the
                Relative Data Depth
		Rebecka Jornsten, Rutgers University

 9:40 - 10:20   On aspects of regression depth and methods based
                on convex risk minimization for data mining
		Andreas Christmann, University of Dortmund, Germany

10:20 - 10:40   Short Break

       Chair:   Suneeta Ramaswami

10:40 - 11:20   Nonparametric clustering of high-dimensional data
                Bogdan Georgescu,  Rutgers University
		Ilan Shimshoni, Technion-Israel Institute of Technology, Israel
 		Peter Meer*, Rutgers University

11:20 - 11:40   Functional Samples and Bootstrap for Predicting SO_2 Levels
		Belen Fernandez-de-Castro*, S.Guillas, W. Gonzalez Manteiga 
		Universidade de Santiago de Compostela, Spain

11:40 - 12:00   Exact, Adaptive, Parallel Algorithms for Data Depth Problems
		Vera Rosta, McGill University, Canada

12:00 - 1:20    Lunch


       Chair:   Peter Rousseeuw
  
 1:20 - 2:00    Analyzing The Number of Samples Required for an
                Approximate Monte-Carlo LMS Line Estimator
		David M. Mount, University of Maryland

 2:00 - 2:40    Optimizing Depth Functions
                Stefan Langerman, Universite Libre de Bruxelles
 
 2:40 - 3:00    Short Break

       Chair:   Peter Rousseeuw
  
 3:00 - 3:40	On the Computation and Robustness of Some Data
                Depth Notions
		Greg Aloupis, McGill University

 3:40 - 5:00    Open Discussion

 5:00           Workshop adjourn

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