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DTSTART:20190331T010000
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DTSTART:20191027T010000
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DTSTART;TZID=Europe/Helsinki:20190408T110000
DTEND;TZID=Europe/Helsinki:20190408T120000
DTSTAMP:20260823T161312
CREATED:20190403T152819Z
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UID:12257-1554721200-1554724800@crest.science
SUMMARY:Rafael Veiel - "Complexity of Strategic Thinking and Robustness of Interim Rationalizability"
DESCRIPTION:CREST Internal Seminar in Microeconomics :  \n\nTime: 11:00 am – 12:00 pm\nDate: 08th May 2019\nPlace: Room 3105.\nRafael Veiel – “Complexity of Strategic Thinking and Robustness of Interim Rationalizability” \nAbstract: In games of incomplete information Interim rationalizability is the equilibrium concept that stems from iterative deletion of dominated strategies. It is known that this solution concept can be sensitive to small misspecifications of players’ beliefs and higher order beliefs. We introduce a measure to capture the complexity of strategic thinking in a game and show that interim rationalizable strategies are robust to perturbations of players’ beliefs as long as they preserve the order of complexity of strategic thinking. \n\n\nOrganizers:\nAlexis Larousse (CREST)\nSponsors:\nCREST\nLunch registration:\nNo registration needed\n\n  \n
URL:https://crest.science/event/rafael-veiel-complexity-of-strategic-thinking-and-robustness-of-interim-rationalizability/
LOCATION:3105
CATEGORIES:Economics
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DTSTART;TZID=Europe/Paris:20190408T140000
DTEND;TZID=Europe/Paris:20190408T151500
DTSTAMP:20260823T161312
CREATED:20190225T101759Z
LAST-MODIFIED:20190225T101759Z
UID:12221-1554732000-1554736500@crest.science
SUMMARY:Asaf WEINSTEIN (Carnegie Mellon University) - "A power analysis for knockoffs using Lasso and thresholded-Lasso statistics"
DESCRIPTION:\nThe Statistical Seminar: Every Monday at 2:00 pm.\nTime: 2:00 pm – 3:15 pm\nDate: 8th of April 2019\nPlace: Room 3001.\nAsaf WEINSTEIN (Carnegie Mellon University) – “A power analysis for knockoffs using Lasso and thresholded-Lasso statistics“ \nAbstract : Practitioners using the Lasso are well aware of its limitations as a variable selector. That good prediction usually leads to many falsely selected variables implies that to capture most of the signal\, one necessarily pays with a high number of false positives. It is also well known that this situation can be mitigated by thresholding the Lasso estimates\, i.e.\, by discarding small estimates one can reduce considerably the number of false selections. \nRecent works have studied both these phenomena from a theoretical perspective in the approximate message-passing (AMP) framework\, providing exact asymptotic predictions for Type I and Type II error rates. These existing works are important because they allow to answer both quantitative and qualitative questions (for example\, where to stop on the Lasso path to ensure FDR\leq \alpha\, or at which value of \lambda should the thresholded Lasso estimates be computed for optimal power?) and compare Lasso to Thresholded Lasso. However\, many of these answers depend on the distribution of the underlying signal. In this talk I’ll focus on our experience with using Knockoffs to mimic these oracle procedures in the absence of knowledge about the signal. It will be demonstrated that the sensitivity of power to the fraction of fake variables added\, is very different for Lasso and for Thresholded Lasso. \n \nOrganizers:\nCristina BUTUCEA\, Alexandre TSYBAKOV\, Julie JOSSE\, Eric MOULINES\, Mathieu ROSENBAUM\nSponsors:\nCREST-CMAP\n \n\n
URL:https://crest.science/event/asaf-weinstein-carnegie-mellon-university/
CATEGORIES:Statistics
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