Laboratoire de Mathématiques de Besançon - UMR 6623 CNRS
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3 décembre 2018: 1 événement

  • Planning des séminaires 2018-2019

    Lundi 3 décembre 11:00-12:00 - Wei Jiang - Centre de mathématiques appliquées (CMAP), École Polytechnique

    Séminaire PS : Adaptive Bayesian SLOPE — High-dimensional Model Selection with Missing Values

    Résumé : Model selection with high-dimensional data becomes an important issue in the last two decades. With the presence of missing data, only a few methods are available to select a model, and their performances are limited. We propose a novel approach – Adaptive Bayesian SLOPE, as an extension of sorted l1 regularization but in Bayesian framework, to perform parameter estimation and variable selection simultaneously in high-dimensional setting. This methodology in particular aims at controlling the False Discovery Rate (FDR). Meanwhile, we tackle the problem of missing data with a stochastic approximation EM algorithm. The proposed methodology is further illustrated by comprehensive simulation studies, in terms of power, FDR and bias of estimation.

    Lieu : Salle 316 - LMB
    En savoir plus : Planning des séminaires 2018-2019