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PSL Summer School on High Dimensional Probability and Algorithms - HDPA 2019

This one week summer school belongs to the PSL-maths program of the PSL university. It is devoted to High dimensional probability and algorithms. The targeted audience is young and less young mathematicians starting from the PhD level. The school took place in ÉNS Paris, from July 1 to 5, 2019.

This school is supported by PSL, CNRS, CEREMADE, ÉNS, and IUF. The organizers are Claire Boyer (Sorbonne Université & ÉNS), Djalil Chafaï (Paris-Dauphine/PSL), and Joseph Lehec (Paris-Dauphine/PSL & ÉNS/PSL). 

The program consists in two 9-hour courses:

Sébastien Bubeck (Microsoft Research) 

Some geometric aspects of randomized online decision making. 

Joel Tropp (California Institute of Technology) 

Random matrix theory and computational linear algebra.

Six 45-minute talks: 

Yohann De Castro (École des Ponts) 

Spectral convergence of random graphs and a focus on random geometric graphs. 

Alexandra Carpentier (U. Potsdam) 

Introduction to some problems of composite and minimax hypothesis testing. 

Olga Klopp (ESSEC / CREST) 

Sparse Network Estimation. 

Laurent Massoulié, (INRIA/Microsoft) 

Planting trees in graphs, and finding them back. 

Nicolas Verzelen (INRA) 

Clustering with the relaxed K-means. 

Lenka Zdeborova (CNRS / CEA Saclay)

Loss landscape and behaviour of algorithms in the spiked matrix-tensor model.

More information on

The video capture was produced technically by Thierry Bohnke and Marianne Herve from OHNK

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