Joint rank and variable selection for parsimonious estimation in a
high-dimensional finite mixture regression model

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Joint rank and variable selection for parsimonious estimation in a high-dimensional finite mixture regression model

2 January 2015

Emilie Devijver

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Papers citing "Joint rank and variable selection for parsimonious estimation in a high-dimensional finite mixture regression model"

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Title
Block-diagonal covariance selection for high-dimensional Gaussian graphical models Emilie Devijver M. Gallopin 60 43 0 12 Nov 2015
Model-based regression clustering for high-dimensional data. Application to functional data Emilie Devijver 65 20 0 04 Sep 2014
Finite mixture regression: A sparse variable selection by model selection for clustering Emilie Devijver 117 26 0 04 Sep 2014
Adaptive Estimation in Two-way Sparse Reduced-rank Regression Zhuang Ma Zongming Ma Tingni Sun 99 34 0 08 Mar 2014
Joint variable and rank selection for parsimonious estimation of high-dimensional matrices F. Bunea Yiyuan She M. Wegkamp 116 114 0 17 Oct 2011
Conditional Density Estimation by Penalized Likelihood Model Selection and Applications Serge Cohen E. L. Pennec 132 30 0 10 Mar 2011
Low rank Multivariate regression Christophe Giraud 180 42 0 27 Sep 2010
Oracle Inequalities and Optimal Inference under Group Sparsity Karim Lounici Massimiliano Pontil Alexandre B. Tsybakov Sara van de Geer 317 381 0 11 Jul 2010
Consistent selection via the Lasso for high dimensional approximating regression models F. Bunea 177 43 0 21 May 2008
Bolasso: model consistent Lasso estimation through the bootstrap Francis R. Bach 93 451 0 08 Apr 2008
Data-driven calibration of penalties for least-squares regression Sylvain Arlot P. Massart 262 159 0 06 Feb 2008