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X-WR-CALDESC:Events for CREST
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DTSTART:20240101T000000
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DTSTART;TZID=UTC:20240506T130000
DTEND;TZID=UTC:20240523T161500
DTSTAMP:20260710T194349
CREATED:20231019T102955Z
LAST-MODIFIED:20240326T092120Z
UID:16124-1715000400-1716480900@crest.science
SUMMARY:Estimation of Functionals of High-Dimensional Parameters: Bias Reduction and Concentration\, Vladimir Koltchinskii (Georgia Institute of Technology)
DESCRIPTION:  \n\n\n\n  \n  \nSCHEDULE\n  \nMonday\n  \n6th May 2024 \n13th May 2024\n  \nFrom 13:00 to 16:15\n  \nRoom 2033\n\n\n  \nThursday\n  \n16th May 2024 \n23rd May 2024\n  \nFrom 13:00 to 16:15\n  \nRoom 2033\n\n\n\nAims and objectives\nThe aim of this course will be on a circle of problems related to estimation of real valued functionals of parameters of high-dimensional statistical models. In such problems\, it is of interest to estimate onedimensional features of a high-dimensional parameter that are often represented by nonlinear functionals of certain degree of smoothness defined on the parameter space. The functionals of interest could be estimated with faster convergence rates than the whole parameter (sometimes\, even with parametric rates). The examples include\, for instance\, such problems as estimation of linear functionals of principal components (that are nonlinear functionals of unknown covariance) in high-dimensional PCA. The goal is to discuss several mathematical methods that provide a way to develop estimators of functionals of highdimensional parameters with optimal error rates in classes of functionals of some Hölder smoothness.\nMoreover\, when the degree of smoothness of the functional is above certain threshold\, the estimators in question have parametric √𝑛 error rate and are asymptotically efficient\, whereas the error rates become slower than √𝑛 when the degree of smoothness is below the threshold.\nThe following topics will be covered (at least\, to some extent):\n• preliminaries in high-dimensional probability and analysis (concentration inequalities\, comparison inequalities\, Hölder smoothness of operator functions\, etc);\n• non-asymptotic bounds and concentration inequalities for sample covariance in high-dimensional and dimension-free frameworks;\n• some approaches to concentration inequalities for smooth functionals of statistical estimators;\n• higher order bias reduction methods in functional estimation;\n– methods based on Taylor expansion and estimation of polynomials with reduced bias;\n– iterative bias reduction and bootstrap chains;\n– linear aggregation of plug-in estimators with different sample sizes and jackknife estimators;\n• minimax lower bounds in functional estimation (applications of van Trees inequality\, Nemirovski’s construction of least favorable functionals\, etc);\n• Examples:\n– high-dimensional and infinite dimensional Gaussian models: functionals of mean and of covariance;\n– log-concave models\, in particular\, log-concave location families;\n– high-dimensional exponential families;\n– nonparametric models\, functionals of unknown density;\n– linear functionals of spectral projections of matrix parameters. \n\n
URL:https://crest.science/event/estimation-of-functionals-of-high-dimensional-parameters-bias-reduction-and-concentration-vladimir-koltchinskii-georgia-institute-of-technology/
LOCATION:2033
CATEGORIES:Doctoral Courses,Statistics
ORGANIZER;CN="Alexandre%20Tsybakov":MAILTO:alexandre.tsybakov@ensae.fr
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240513
DTEND;VALUE=DATE:20240518
DTSTAMP:20260710T194349
CREATED:20240514T073119Z
LAST-MODIFIED:20240514T073119Z
UID:17019-1715558400-1715990399@crest.science
SUMMARY:6th Workshop on Sequential Monte Carlo Methods (SMC 2024)
DESCRIPTION:13 – 17 May 2024 \nWith the paprticipation of Nicolas Chopin \nhttps://www.icms.org.uk/SMC2024 \n
URL:https://crest.science/event/6th-workshop-on-sequential-monte-carlo-methods-smc-2024/
CATEGORIES:Conferences and Workshops,Statistics
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20240515T121500
DTEND;TZID=Europe/Helsinki:20240515T133000
DTSTAMP:20260710T194349
CREATED:20240423T070354Z
LAST-MODIFIED:20240426T123346Z
UID:16989-1715775300-1715779800@crest.science
SUMMARY:Luca BRAGHIERI (Universita'Bocconi) - “TBA"
DESCRIPTION:Séminaire Microéconomie : Tous les mercredis\nHeure : 12h15 – 13h30\nDate : 15/05/2024\nSalle : 3001 \nLuca BRAGHIERI (Universita’Bocconi) – “TBA” \nCV : TBA \nOrganisateurs : \nJulien COMBE (Pôle d’Economie du CREST)\n​​​​​​​​​​​​Yves Le YAOUNQ (Pôle d’Economie du CREST)\n​​​​​​​​​Matias NUNEZ (Pôle d’Economie du CREST) \nCommanditaires :\nCREST \n
URL:https://crest.science/event/luca-braghieri-universitabocconi-tba/
CATEGORIES:Microeconomics,Seminars
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