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Cours magistraux

le (56m12s)

## Tropp 6/9 - Random matrix theory and computational linear algebra

This course treats some contemporary algorithms from computational linear algebra that involve random matrices. Rather than surveying the entire field, we focus on a few algorithms that are both simple and practically useful. We begin with an introduction to matrix concentration inequalities, which are a powerful tool for analyzing structured random matrices. We use these ideas to study matrix approximations constructed via randomized sampling, such as the random features method. As a more sophisticated application, we present a complete treatment of a recent algorithm for solving graph Laplacian linear systems in near-linear time. Some references : 1. Tropp, "An introduction to ...
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Cours magistraux

le (0s)

## Tropp 7/9 - Random matrix theory and computational linear algebra

This course treats some contemporary algorithms from computational linear algebra that involve random matrices. Rather than surveying the entire field, we focus on a few algorithms that are both simple and practically useful. We begin with an introduction to matrix concentration inequalities, which are a powerful tool for analyzing structured random matrices. We use these ideas to study matrix approximations constructed via randomized sampling, such as the random features method. As a more sophisticated application, we present a complete treatment of a recent algorithm for solving graph Laplacian linear systems in near-linear time. Some references : 1. Tropp, "An introduction to ...
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Cours magistraux

le (1h24m41s)

## Tropp 8/9 - Random matrix theory and computational linear algebra

This course treats some contemporary algorithms from computational linear algebra that involve random matrices. Rather than surveying the entire field, we focus on a few algorithms that are both simple and practically useful. We begin with an introduction to matrix concentration inequalities, which are a powerful tool for analyzing structured random matrices. We use these ideas to study matrix approximations constructed via randomized sampling, such as the random features method. As a more sophisticated application, we present a complete treatment of a recent algorithm for solving graph Laplacian linear systems in near-linear time. Some references : 1. Tropp, "An introduction to ...
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Cours magistraux

le (41m0s)

## Tropp 9/9 - Random matrix theory and computational linear algebra

This course treats some contemporary algorithms from computational linear algebra that involve random matrices. Rather than surveying the entire field, we focus on a few algorithms that are both simple and practically useful. We begin with an introduction to matrix concentration inequalities, which are a powerful tool for analyzing structured random matrices. We use these ideas to study matrix approximations constructed via randomized sampling, such as the random features method. As a more sophisticated application, we present a complete treatment of a recent algorithm for solving graph Laplacian linear systems in near-linear time. Some references : 1. Tropp, "An introduction to ...
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Conférences

le (50m34s)

## Le numérique stade suprême du capitalisme ? L'économie politique à l'ère des plateformes

Réseaux en société, sociétés en réseau, Le Centre Internet et Société (CIS) est un centre de recherche créé par le CNRS en 2019. Au croisement de disciplines telles que la sociologie, le droit, l'histoire, l'économie, la science politique, les sciences de l'information et de la communication, l'informatique et les sciences de l'ingénieur, le CIS entend construire une recherche et une expertise indépendantes et interdisciplinaires, capables d'éclairer les grandes controverses techniques et la définition des politiques contemporaines liées au numérique, à l'internet, et plus largement à l'informatique.Table ronde. Le numérique stade suprême du capitalisme ? L'économie politique à l'ère ...
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