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DTSTART;TZID=Europe/Paris:20201109T140000
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SUMMARY:Gil KUR (MIT) - " On the Minimax Optimality of the Maximum Likelihood in the non-Donsker regime "
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 9th of November 2020\nPlace: Visio\nGil KUR (MIT)  – ” On the Minimax Optimality of the Maximum Likelihood in the non-Donsker regime “ \nAbstract: The minimax optimality of the Maximum Likelihood Estimator (MLE) is a fundamental question in mathematical statistics. For Donsker classes\, it is well-known that the MLE is minimax optimal. However\, in the non-Donsker regime\, the MLE could be minimax sub-optimal. In this talk\, we present new techniques to evaluate the statistical performance of the MLE in the non-Donsker regime. As an application\, we demonstrate that the log-concave MLE is optimal in all dimensions. In comparison\, for convex regression\, the MLE can be suboptimal when $d \ge 5$. \nThis talk is based on joint work with Dagan\, Gao\, Guntuboyina\, Rakhlin and Sen. \nOrganizers:\nCristina BUTUCEA (CREST)\, Alexandre TSYBAKOV (CREST)\, Karim LOUNICI (CMAP) \, Zoltan SZABO (CMAP)\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/gil-kur/
CATEGORIES:Statistics
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