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Parameter-Free High-Dimensional Screening Using Multiple Grouping of Variables
Parameter-Free High-Dimensional Screening Multiple Grouping Variables
2012/9/17
Screening is the problem of estimating a superset of the set of non-zero entries in an unknownp-dimensional vector β given nnoisy observations. In the high-dimensional regime, where p > n, screening a...
Grouping Strategies and Thresholding for High Dimensional Linear Models
Structured sparsity Grouping, Learning Theory Non Linear Methods Block-thresholding coherence Wavelets
2012/9/19
The estimation problem in a high regression model with structured sparsity is investigated.An algorithm using a two steps block thresholding procedure called GR-LOL is provided.Convergence rates are p...
In the literature surrounding Bayesian penalized regression, the two primary choices of
prior distribution on the regression coecients are zero-mean Gaussian and Laplace. While
both have been compa...