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[Sy-cg-global] [Publicity-list] DIMACS Workshop on Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications

Linda Casals lindac at dimacs.rutgers.edu
Wed May 7 14:18:07 EDT 2003


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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 at stat.rutgers.edu 

  Robert Serfling
     University of Texas at Dallas
     serfling at utdallas.edu 
     
  Diane Souvaine
    Tufts University
    dls at eecs.tufts.edu 
     
  Yehuda Vardi
    Rutgers University
    vardi at stat.rutgers.edu 

Presented under the auspices of the DIMACS Special Focus on Data
Analysis and Mining and the DIMACS Special Focus on Computational
Geometry and Applications.

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Multivariate statistical methodology plays a role of ever increasing
importance in real life applications, which typically entail a host of
interrelated variables. Simple extensions of univariate statistics to
the multivariate setting do not properly capture the
higher-dimensional features of multivariate data, nor do they yield
geometric solutions because of the absence of a natural order for
multidimensional Euclidean space. A more promising approach is the one
based on "data depth", which can provide a center-outward ordering of
points in Euclidean space of any dimension. Extensive developments in
recent years have generated many attractive depth-based tools for
multivariate data analysis, with a wide range of applications. The
diversity in approaches, emphases, and concepts, however, makes it
necessary to seek unified views and perspectives that would guide the
further development of the depth-based approach.

The concept of data depth provides new perspectives to probabilistic
as well as computational geometries. In particular, the development of
implementable computing algorithms for depth-based statistics has
brought about many new challenges in computational geometry. This
workshop would create a unique environment for multidisciplinary
collaboration among computer scientists, theoretical and applied
statisticians, and data analysts. It would bring together active
researchers in these fields to discuss significant open issues,
establish perspective on applications, and set directions for further
research.

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STUDENT SCHOLARSHIPS:

The workshop offers some student scholarships to reimburse expenses
for travel, registration, and lodging at the workshop, up to
$400. Applicants for student scholarships should contact Regina Liu
(rliu at stat.rutgers.edu).

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Wednesday, May 14, 2003

 8:00 -  9:00   Breakfast and registration

 9:00  - 9:10   Opening remarks
                Fred Roberts, 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 -  1:30   Lunch

       Chair:   Xuming He

 1:30 -  2:10   Data Analysis by Zonoid Depth 
	        Karl Mosler, Universitat zu Koln, Germany

 2:10 -  2:50	Data Depth in Multivariate Analysis:
                Dependence, Discrimination and Clustering
	        Mario Romanazzi, "Ca' Foscari University of Venice, Italy

 2:50 -  3:10   Fast Algorithms for Frames and Point Depth
                in Polyhedral Hulls
		Jose Dula, University of Mississippi and the U.S. Census Bureau

 3:10 -  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)


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 -  2:00   Lunch
       
       Chair:   Evarist Gine

 2:00 -  2:40   On data based distances between
		data vectors and between hyperplanes
		Hannu Oja, University of Jyvaskyla, Finland

 2:40 -  3:20   On the Computation and Robustness of Some Data
                Depth Notions
		Greg Aloupis, McGill University

 3:20 -  4:00   Yehuda Vardi
                Deep Talk

 4:00 -  4:30   Break

       Chair:   David Tyler

 4:30 -  4:50   A definition of depth for functional observations
		Sara López-Pintado, Juan Romo*
		Universidad Carlos III de  Madrid, Spain 

 4:50 -  5:10	A Depth_Based Kurtosis Functional  
 		Jin Wang, University of Texas at Dallas

 5:10 -  5:50   Tukey depth-based trimmed means
                Jean-Claude Masse, Universite Laval, Quebec, Canada

 6:20           DINNER, DIMACS Lounge


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    A note on Simplicial Depth &
                Software Demonstration
                Michael Burr*, Eynat Rafalin*, Diane Souvaine, Tufts University

 3:40 - 5:00    Open Discussion

 5:00           Workshop adjourn


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Registration Fees: 

(Pre-registration deadline: May 7, 2003) 

Regular rate
Preregister before deadline $100/day
After preregistration deadline $120/day

Reduced Rate*
Preregister before deadline $50/day
After preregistration deadline $60/day

Postdocs
Preregister before deadline $10/day
After preregistration deadline $15/day

DIMACS Postdocs $0

Non-Local Graduate & Undergraduate students
Preregister before deadline $5/day
After preregistration deadline $10/day

Local Graduate & Undergraduate students $0
(Rutgers & Princeton)

DIMACS partner institution employees** $0

DIMACS long-term visitors*** $0

Registration fee to be collected on site, cash, check, VISA/Mastercard
accepted.

Our funding agencies require that we charge a registration fee for the
workshop. Registration fees cover participation in the workshop, all
workshop materials, breakfast, lunch, breaks, and any scheduled social
events (if applicable).

* College/University faculty and employees of non-profit organizations
will automatically receive the reduced rate. Other participants may
apply for a reduction of fees. They should email their request for the
reduced fee to the Workshop Coordinator at
workshop at dimacs.rutgers.edu.  Include your name, the Institution you
work for, your job title and a brief explanation of your situation.
All requests for reduced rates must be received before the
preregistration deadline. You will promptly be notified as to the
decision about it.

** Fees for employees of DIMACS partner institutions are waived.
DIMACS partner institutions are: Rutgers University, Princeton
University, AT&T Labs - Research, Bell Labs, NEC Laboratories America
and Telcordia Technologies. Fees for employees of DIMACS affiliate
members Avaya Labs, IBM Research and Microsoft Research are also
waived.

***DIMACS long-term visitors who are in residence at DIMACS for two or
more weeks inclusive of dates of workshop.


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Information on participation, registration, accommodations, and travel
can be found at:

    http://dimacs.rutgers.edu/Workshops/Depth/
  
     **PLEASE BE SURE TO PRE-REGISTER EARLY**

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