Covariance structure approximation via gLasso in high-dimensional supervised classification
T Pavlenko, A Björkström, A Tillander - Journal of Applied Statistics, 2012 - Taylor & Francis
Recent work has shown that the Lasso-based regularization is very useful for estimating the
high-dimensional inverse covariance matrix. A particularly useful scheme is based on …
high-dimensional inverse covariance matrix. A particularly useful scheme is based on …
Estimation in high-dimensional analysis and multivariate linear models
T Kollo, T Von Rosen, D Von Rosen - Communications in Statistics …, 2011 - Taylor & Francis
This article presents a new approach of estimating the parameters describing the mean
structure in the Growth Curve model when the number of variables compared with the …
structure in the Growth Curve model when the number of variables compared with the …
Exploiting sparse dependence structure in model based classification
T Pavlenko, A Björkström - … Soft Computing and Statistical Methods in Data …, 2010 - Springer
AISC 77 - Exploiting Sparse Dependence Structure in Model Based Classification Page 1
Exploiting Sparse Dependence Structure in Model Based Classification Tatjana Pavlenko and …
Exploiting Sparse Dependence Structure in Model Based Classification Tatjana Pavlenko and …
Scoring feature subsets for separation power in supervised Bayes classification
T Pavlenko, H Fridén - Soft Methods for Integrated Uncertainty Modelling, 2006 - Springer
We present a method for evaluating the discriminative power of compact feature
combinations (blocks) using the distance-based scoring measure, yielding an algorithm for …
combinations (blocks) using the distance-based scoring measure, yielding an algorithm for …
[PDF][PDF] Estimation in high-dimensional analysis and multivariate linear models
T Kollo, T von Rosen, D von Rosen - 2008 - slu.se
When the number of variables compared with the number of observations is large this paper
presents a new approach of estimating the parameters describing the mean structure in the …
presents a new approach of estimating the parameters describing the mean structure in the …