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February 10, 2020
February 11, 2020(1 event)

Distributed Variational Representation Learning, by Abdellatif Zaidi (Huawei)


February 11, 2020

We connect the information flow in a neural network to sufficient statistics; and show how techniques that are rooted in information theory, such as the source-coding based information bottleneck method can lead to improved architectures, as well as a better understanding of the theoretical foundation of neural networks, viewed as a cascade compression network. We discuss distributed architectures and illustrate our results and view through some numerical examples.

February 12, 2020
February 13, 2020(1 event)

Seminar Francois Durand: "Analysis of Approval Voting in Poisson Games"


February 13, 2020

Titre : 
Analysis of Approval Voting in Poisson Games
Résumé :

Poisson games were introduced by Roger Myerson to model large elections. In this framework, the number of players of each type follows a Poisson distribution. Typically, the expected number of players is considered large, and players base their strategic response on rare events, such as a "pivot" where two candidates are tied for victory, and where one vote can make the difference. The main part of the talk will be dedicated to presenting Poisson games and the main theoretical results about them. Then I will say a few words about our work on a voting rule called Approval voting.

References:
R. Myerson (2000). Large Poisson games. Journal of Economic Theory, 94, 7–45.
R. Myerson (2002). Comparison of scoring rules in Poisson voting games. Journal of Economic Theory, 103, 219–251.
F. Durand, A. Macé and M. Núñez (2019). Analysis of Approval Voting in Poisson Games. ACM Conference on Economics and Computation.

Python implementation: https://poisson-approval.readthedocs.io/.

February 14, 2020
February 15, 2020
February 16, 2020

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