Conférence de Cristopher Moore lors du colloquium Data Science Colloquium of the ENS
This colloquium is organized around data sciences in a broad sense, with the goal of bringing together researchers with diverse backgrounds (including mathematics, computer science, physics, chemistry and neuroscience) but a common interest in dealing with large scale or high dimensional data.
There is a deep analogy between statistical inference and statistical physics; I will give a friendly introduction to both of these fields. I will then discuss phase transitions in two problems of interest to a broad range of data sciences: community detection in social and biological networks, and clustering of sparse high-dimensional data. In both cases, if our data becomes too sparse or too noisy, it suddenly becomes impossible to find the underlying pattern, or even tell if there is one. Physics both helps us locate these phase transiitons, and design optimal algorithms that succeed all the way up to this point. Along the way, I will visit ideas from computational complexity, random graphs, random matrices, and spin glass theory.
Catégories: Data Science Colloquium
Mot-clés : base de données, informatique, algorithme, interdisciplinarité, interprétation, physique statistique, ordinateur, intelligence artificielle, inférence statistique
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Cursus :
Cristopher David Moore, connu sous le nom de Cris Moore est un informaticien américain, mathématicien et physicien. Il est professeur à l'Institut de Santa Fe et a été professeur à l'Université du Nouveau-Mexique.
Cliquer ICI pour fermerDernière mise à jour : 22/10/2020
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