We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
Abstract-- Increasing delay and power variation are significant challenges to the designers as technology scales to the deep sub-micron (DSM) regime. Traditional module selection t...
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approa...