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Minimax risks for sparse regressions: Ultra-high-dimensional phenomenons
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Minimax risks for sparse regressions: Ultra-high-dimensional phenomenons

Nicolas Verzélen
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Papers citing "Minimax risks for sparse regressions: Ultra-high-dimensional phenomenons"

4 / 4 papers shown
Title
Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism
Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism
E. Arias-Castro
Emmanuel J. Candès
Y. Plan
98
211
0
08 Jul 2010
Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing
Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing
D. Donoho
Jared Tanner
94
465
0
14 Jun 2009
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
Karim Lounici
496
243
0
30 Jan 2008
Goodness-of-fit Tests for high-dimensional Gaussian linear models
Goodness-of-fit Tests for high-dimensional Gaussian linear models
Nicolas Verzélen
Fanny Villers
153
35
0
14 Nov 2007

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