[Statlist] Seminar ueber Statistik

[Christina Kuenzli]

                       ETH and University of Zurich 
      Proff. A.D. Barbour -- P. Buehlmann -- F. Hampel -- H.R. Kuensch 

**************************************************************************
           We are pleased to announce the following seminars
**************************************************************************
Friday, January 23, 2004,  15.15 h, LEO C 15 

    Christian Robert, CEREMADE, Universite Paris Dauphine

    Population Monte Carlo Methods, 
**************************************************************************
Friday, January 30, 2004,  15.15 h, LEO C 15

    David J. Hand, Imperial College London

    Pattern discovery and detection

Modern statistical data analysis is predominantly model-driven, seeking
to decompose an observed data distribution in terms of major underlying
descriptive features modified by some stochastic variation.  A large
part of data mining is also concerned with this exercise.  However,
another fundamental part of data mining is concerned with detecting
anomalies amongst the vast mass of the data: the small deviations,
unusual observations, unexpected clusters of observations, or surprising
blips in the data, which the model does not explain.  We call such
anomalies patterns.   For sound reasons, which are outlined in the
paper, the data mining community has tended to focus on the algorithmic
aspects of pattern discovery, and has not developed any general
underlying theoretical base.  However, such a base is important for any
technology: it helps to steer the direction in which the technology
develops, as well as serving to provide a basis from which algorithms
can be compared, and to indicate which problems are the important ones
waiting to be solved.  This paper attempts to provide such a theoretical
base, linking the ideas to statistical work in spatial epidemiology,
scan statistics, outlier detection, and other areas.  One of the
striking characteristics of work on pattern discovery is that the ideas
have been developed in several theoretical arenas, and also in several
application domains, with little apparent awareness of the fundamentally
common nature of the problem.  Like model building, pattern discovery is
fundamentally an inferential activity, and is an area in which
statisticians can make very significant contributions.
---------------------------------------------------------------------

(LEO (Leonhardstrasse 27, 8006 Zurich) is close to the main building,
across the hill-side station of the 'Polybahn') 
Overview maps of ETH : http://www.ethz.ch/search/orientation_en.asp

Further information: Christina Kuenzli, Statistics Seminar of ETH Zurich 
**************************************************************************

Everybody is kindly invited
 
Eidgenoessische Technische Hochschule Zuerich
Swiss Federal Insitute of Technology Zurich
________________________________________________________
Christina Kuenzli            <kuenzli using stat.math.ethz.ch>
Seminar fuer Statistik      
Leonhardstr. 27,  LEO D11          phone: +41 1 632 3438         
ETH-Zentrum,                       fax  : +41 1 632 1228 
CH-8092 Zurich, Switzerland        http://stat.ethz.ch/~