11h30-12h30 Wednesday, August 25

Chairman : Gilbert Saporta   Room: Paul Painlevé
Luc Devroye, School of Computer Science, McGill University, Montreal
"Complexity questions in non-uniform random variate generation"
I will discuss the sub-discipline of random variate generation, starting from the pioneering fifties, and ending with the challenges that lie ahead.

11h-12h Friday, August 27
Chairman : Stan Azen   Room: Paul Painlevé
Lutz Edler, Division of Biostatistics, German Cancer Research Center, Heidelberg
"Computational Statistics Solutions for Modern Biomedical Research: A Challenge and Chance for Both"
The talk will address how computational statistics, computing power, data analysis and data interpretation has invaded in a very short time many cutting edge research areas of modern biomedicine and biomedical research. Which are consequences for both sides when they want to be partners in successful projects? The challenging areas are not at all restricted to the genomic and post genomic molecular data but reach far more out into all fields of diagnosis, prognosis and outcome prediction of diseases and their treatment. This includes complex designs as well as the efficient use of image data. The lecture will demonstrate successes fields, elaborate challenges and also point out computing needs to communicate computing.

9h30-10h30 Monday, August 23
Chairman : Patrick Groenen   Room: Paul Painlevé
David Hand Statistics Section, Imperial College, London
"The laws of Coincidence"
Anomalous events often lie at the roots of discoveries in science or actions in other domains.  Familiar examples are the discovery of pulsars, the identification of the initial signs of an epidemic, and the detection of faults.  In general, they are events which are seen as so unexpected or improbable that one suspects there must be some underlying cause.  One particular kind of anomalous event is the coincidence, defined by Diaconis and Mosteller (1989) a `a surprising concurrence of events, perceived as meaningfully related, with no apparent causal connection'.
The search for explanations - for the causal connections - has led to superstitions, beliefs in gods, fate, synchronicity, and other representations of the notion that there are unseen forces guiding our destiny.  These might be characterised as `prescientific explanations' as they rely on forces which do not have the observed empirical infrastructure of physical forces, such as gravity or magnetism, as well as social and behavioural forces such as Adam Smith's invisible hand.
While one can never prove that there are no such forces (one can prove a presence, but never an absence), closer examination shows that in many cases one should in fact expect apparent `coincidences' to occur.  This explanation can be conveniently couched in terms of a number of laws.  Since these laws are concerned with what are perceived as unusual data configurations and events, they can be seen as serving a role complementary to familiar statistical laws covering mass phenomena, such as the law of large numbers, and principles which derive from this, such as the laws of statistical mechanics and thermodynamics in physics and many laws in economics and the social sciences. These laws describing the origin of coincidences include:the law of total probability, the law of truly large numbers, the law of near enough, the law of search, the law of the lever, the law ofthe tortoise, and the law of selection.
These laws are defined and illustrated with a series of examples. The implications for anomaly detection methods are discussed.