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X-WR-CALDESC:Events for CREST
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DTSTART:20190331T010000
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DTSTART:20191027T010000
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DTSTART:20190331T010000
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DTSTART;TZID=Europe/Helsinki:20191106T001500
DTEND;TZID=Europe/Helsinki:20191106T133000
DTSTAMP:20260817T013229
CREATED:20190826T123324Z
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SUMMARY:Harry Di Pei (Northwestern University) - "Reputation Building with Endogenous Speed of Learning"
DESCRIPTION:CREST Microeconomics Seminar :  \n\nTime: 12:15 pm – 1:30pm\nDate: 6th Nov. 2019\nPlace: Room 3001.\nHarry Di Pei (Northwestern University) – Reputation Building with Endogenous Speed of Learning\nAbstract: “I study reputation models where each short-run player observes a (possibly stochastic) bounded subset of the long-run player’s previous period  actions\, in addition to the entire history of her predecessors’ actions. Reputation effects fail because the speed of learning decreases endogenously with the long-run player’s patience. When each short-run player can also observe an informative signal about the long-run player’s current period action\, I propose a resistent to learning condition under which reputation effects fail. This is because the short-run player’s action can be uninformative about the long-run player’s type in periods where the latter receives a low stage-game payoff. When the environment is not resistent to learning\, the patient long-run player can secure his  commitment payoff in all equilibria. I explain the differences between my resistent to learning condition and the bounded informativeness condition in  observational learning models.” \nOrganizers: \n\n\nRoxana Fernandez Machado (CREST)\, Marie Laure Allain (CREST)\, and Linda Schilling (CREST)\nSponsors:\nCREST\nLunch registration:\nfood provided\, no registration needed\n\n  \n
URL:https://crest.science/event/harry-di-pei-northwestern-university-reputation-building-with-endogenous-speed-of-learning/
LOCATION:3001
CATEGORIES:Microeconomics
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DTSTART;TZID=Europe/Paris:20191106T140000
DTEND;TZID=Europe/Paris:20191106T150000
DTSTAMP:20260817T013229
CREATED:20191030T073101Z
LAST-MODIFIED:20191030T073101Z
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SUMMARY:Badr-Eddine CHERIEF-ABDELLATIF(CREST) - "Theoretical Study of Variational Inference"
DESCRIPTION:\nThe Stats-Machine Learning-Econometrics Seminar.\nTime: 14:00 pm – 15:00 pm\nDate: 6th of November 2019\nPlace: Room 3001.\nBadr-Eddine CHERIEF-ABDELLATIF(CREST) – “Theoretical Study of Variational Inference”\n Abstract : Bayesian inference provides an attractive learning framework to analyze and to sequentially update knowledge on streaming data\, but is rarely computationally feasible in practice. In the recent years\, variational inference (VI) has become more and more popular for approximating intractable posterior distributions in Bayesian statistics and machine learning. Nevertheless\, despite promising results in real-life applications\, only little attention has been put in the literature towards the theoretical properties of VI. In this talk\, we aim to present some recent advances in theory of VI. First\, we show that variational inference is consistent under mild conditions and retains the same properties than exact Bayesian inference in the batch setting. Then\, we study several online VI algorithms that are inspired from sequential optimization in order to compute the variational approximations in an online fashion. We provide theoretical guarantees by deriving generalization bounds and we present empirical evidence in support of this.\n\n\n\nSponsors:\nCREST\n\n\n
URL:https://crest.science/event/badr-eddine-cherief-abdellatif/
LOCATION:ENSAE Paris\, 5\, avenue Henry Le Chatelier\, 91120 Palaiseau\, France
CATEGORIES:Economics,Statistics
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