Organizing Committee:
Hélène Massam (University of Virginia), David Tritchler (University
of Toronto)
Scientific Committee:
Phil Dawid (University College, London),
Steffen Lauritzen (Aalborg University),
Michael Perlman (University of Washington)
The aim of this research program is threefold:
- To bring together a group of eminent researchers in subdisciplines
of Statistics, Probability, Algebra, Artificial Intelligence, and
some areas of applications to improve on the current understanding
of the basic structures of Highly Structured Stochastic Systems (HSSS)
models.
- To train graduate students in statistics, and researchers in areas
of applications, in newly developed techniques. It is particularly
important that graduate students be exposed to a variety of disciplines
involved in the study of HSSS so that they may take a multidisciplinary
approach in their research. In such workshops, students should also
update their computational skills to be able to use and understand
some of the most recent computational methods.
- To offer short courses, applicable to business, medical or social
sciences, to introduce already developed software to non-specialists
who are in decision-making positions (i.e. epidemiologists, consultants
in investments, sociologists, etc.)
The following courses are aimed at graduate students, session participants
and non-specialists in statistics:
SEPTEMBER 20 - OCTOBER 22, 1999
Course 1: Graphical Markov Models
Steen Andersson (Indiana University)
SEPTEMBER 20 - OCTOBER 1, 1999
Course 2: Linear Structural Equations and Graphical Models
Jan Koster (Erasmus University)
OCTOBER 27 - OCTOBER 29, 1999
Short Course 1: Diagnosing and Planning with Bayesian Networks and
Influence Diagrams (A Practical Guide)
Uffe Kjærulff (Aalborg University) and Kristian Olesen (Aalborg University)
NOVEMBER 15 - NOVEMBER 16, 1999
Short Course 2: Graphical Markov Models: Their Role in Statistical
Analysis of Data Generating Processes
David Cox (Nuffield College, Oxford) and Nanny Wermuth (ZUMA - Center
for Survey Research, Mannheim)
LECTURES -- SEWALL WRIGHT LECTURE SERIES
Judea Pearl (University of California)
"The Mathematics
of Cause and Effect"
October 25, 3:30 p.m. to 5:30 p.m.
October 26, 3:00 p.m. to 5:00 p.m.
Glenn Shafer (Rutgers University)
"The Language of Causality"
November 4, 3:30 p.m. to 5:30 p.m.
November 9, 3:30 p.m. to 5:30 p.m.
For experts in the different fields represented, we plan longer
research seminars discussing the latest developments:
SEPTEMBER 27 - OCTOBER 8, 1999
Seminar 1: Causal Interpretation of Graphical Models
Phil Dawid (University College, London) and Glenn Shafer (Rutgers
University)
OCTOBER 11 - 29, 1999
Seminar 2: Relating Causal Structure to Conditional
Independence Structure
Thomas Richardson (University of Warwick) and Peter Spirtes (Carnegie
Mellon University)
NOVEMBER 2 - 12, 1999
Seminar 3: Learning Causal Models
David Heckerman (Microsoft Research) and Steffen Lauritzen (Aalborg
University)
SEPTEMBER 27 - OCTOBER 15, 1999
Seminar 4: Conditional Independence Structures
Milan Studený and Frantisek Matús (Academy of Science of Czech Republic)
OCTOBER 25 - NOVEMBER 12, 1999
Seminar 5: Algebraic Methods in Graphical Markov Models
Steen Andersson (Indiana University), Gérard Letac (Université Paul
Sabatier), Michael Perlman, (University of Washington) and Hélène
Massam (University of Virginia)