Events in March–April 2020
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February 24, 2020
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February 25, 2020
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February 26, 2020
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February 27, 2020(1 event)
Strategic information transmission with receiver's type-dependent decision sets, by Stephan Sémirat (GAEL, Grenoble)Strategic information transmission with receiver's type-dependent decision sets, by Stephan Sémirat (GAEL, Grenoble) – Strategic information transmission with receiver's type-dependent decision sets. Abstract: We consider a sender-receiver game, in which the sender has finitely many types and the receiver makes decisions in a bounded real interval. We assume that utility functions are concave, single-peaked and supermodular. After the cheap talk phase, the receiver makes a decision, which must fulfill a constraint (e.g., a participation constraint) that depends on the sender's type. Hence a necessary equilibrium condition is that the receiver maximizes his expected utility subject to the constraints of all positive probability types. This necessary condition may not hold at the receiver's prior belief, so that a non-revealing equilibrium may fail to exist. We propose a constructive algorithm that always achieves a partitional perfect Bayesian equilibrium Bâtiment IMAG (442) |
February 28, 2020
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February 29, 2020
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MarchMarch 1, 2020 |
March 2, 2020
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March 3, 2020
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March 4, 2020
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March 5, 2020(1 event)
keynote LIGkeynote LIG – |
March 6, 2020
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March 7, 2020
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March 8, 2020
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March 9, 2020
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March 10, 2020
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March 11, 2020
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March 12, 2020(1 event)
Seminar Anastasios GiovanidisSeminar Anastasios Giovanidis – Title : Ranking Online Social Users by their Influence Abstract: In this talk I will introduce an original mathematical model to analyse the diffusion of posts within a generic online social platform. As a main result, using the developed model, we derive in closed form the probabilities that posts originating from a given user are found on the Wall and Newsfeed of any other inside the platform. By combining these probabilities we get a measure of per user influence on the entire network. This constitutes a new centrality measure which is more expressive than existing ones, in the sense that it combines the user position on the graph with the user posting activity. Comparisons with simulations show the accuracy of this model and its robustness with respect to the modelling assumptions. Furthermore, its application on large data traces from real platforms asserts its validity for real world applications, and the possibilities it opens for explaining real diffusion phenomena and predicting actual user influence.
Bio: |
March 13, 2020(1 event)
F. Falniowski: "Robust routes to chaos in congestion games: The effects of scale on learning dynamics"F. Falniowski: "Robust routes to chaos in congestion games: The effects of scale on learning dynamics" – We study the effects of increasing the population size/scale of costs in congestion games and generalize recent results for the well known Multiplicative Weights Update dynamic to a large class of Follow-the-Regularized Leader dynamics (FoReL). We prove that even in simple linear congestion games with two parallel links as the population/scale increases, learning becomes unstable and (unless the game is fully symmetric) eventually Li-Yorke chaotic. Despite their chaotic instability, the dynamics provably converge in a time-average sense to an exact equilibrium for any choice of learning rate and any scale of costs. |
March 14, 2020
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March 17, 2020
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March 18, 2020
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March 19, 2020(1 event)
Seminar CERAI Alexandre TermierSeminar CERAI Alexandre Termier – |
March 20, 2020
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March 21, 2020
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March 22, 2020
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March 23, 2020
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March 24, 2020
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March 25, 2020
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March 26, 2020(1 event)
PhD defense of Stephan Plassart (Postponed due to COVID lockdown)PhD defense of Stephan Plassart (Postponed due to COVID lockdown) – TBA |
March 27, 2020
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March 28, 2020
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March 29, 2020
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March 30, 2020
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March 31, 2020
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AprilApril 1, 2020 |
April 2, 2020(2 events)
keynote LIGkeynote LIG – POLARIS theory meetingPOLARIS theory meeting – |
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April 14, 2020
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April 15, 2020
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April 24, 2020
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April 26, 2020
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April 27, 2020
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April 28, 2020
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MayMay 1, 2020 |
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May 3, 2020
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- March 26, 2024 @ Bâtiment IMAG (442) -- [Seminar] Romain Cravic
Who: Romain Cravic
When: Tuesday, March 26, 14:00-15:00
Where: IMAG 406
What: Résoudre les jeux partiellement observables : Algorithme CFR et variantes de Monte-Carlo, deuxième partie
More: Dans ce séminaire en deux parties, je vous présenterai la famille des algorithmes CFR (CounterFactual Regret minimization) appliqués aux jeux sous forme extensive à information incomplète. CFR a été utilisé en 2015 par des chercheurs de l’université d’Alberta pour résoudre une version « réaliste » du poker (Heads-up limit poker). Dans la première partie nous verrons comment modéliser l’information incomplète pour les jeux à deux joueurs à somme nulle, comment définir des stratégies dans ce modèle, avant d’analyser en détail l’algorithme CFR qui calcule un approximation de l’équilibre de Nash du jeu. Pour aller plus loin, dans la seconde partie, nous étudierons les variantes dites « Monte-Carlo » de l’algorithme CFR qui sont indispensables quand on souhaite trouver des bonnes stratégies dans des jeux plus ambitieux.
- April 3, 2024 @ Bâtiment IMAG (442) -- [Seminar] Victor Boone
Who: Victor Boone
When: Wednesday, April 3, 14:00-15:00
Where: 447
What: Learning MDPs with Extended Bellman Operators
More: Efficiently learning Markov Decision Processes (MDPs) is difficult. When facing an unknown environment, where is the adequate limit between repeating actions that have shown their efficiency in the past (exploitation of your knowledge) and testing alternatives that may actually be better than what you currently believe (exploration of the environment)? To bypass this dilemma, a well-known solution is the "optimism-in-face-of-uncertainty" principle: Think of the score of an action as being the largest that is statistically plausible.
The exploration-exploitation dilemma then becomes the problem of tuning optimism. In this talk, I will explain how optimism in MDPs can be all rephrased using a single operator, embedding all the uncertainty in your environment within a single MDP. This is a story about "extended Bellman operators" and "extended MDPs", and about how one can achieve minimax optimal regret using this machinery.
- April 11, 2024 @ Bâtiment IMAG (442) -- [Seminar] Charles Arnal
Who: Charles Arnal
When: Thursday, April 11, 14:00-15:00
Where: 442
What: Mode Estimation with Partial Feedback
More: The combination of lightly supervised pre-training and online fine-tuning has played a key role in recent AI developments. These new learning pipelines call for new theoretical frameworks. In this paper, we formalize core aspects of weakly supervised and active learning with a simple problem: the estimation of the mode of a distribution using partial feedback. We show how entropy coding allows for optimal information acquisition from partial feedback, develop coarse sufficient statistics for mode identification, and adapt bandit algorithms to our new setting. Finally, we combine those contributions into a statistically and computationally efficient solution to our problem.
- April 30, 2024 @ Bâtiment IMAG (442) -- Seminar Rémi Castera
Correlation of Rankings in Matching Markets