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...
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
Abstract. A resource selection probability function is a function that gives the probability that a resource unit (e.g., a plot of land) that is described by a set of habitat varia...
Feature design and feature selection are two key problems in facial image based age perception. In this paper, we proposed to using ranking model to do feature selection on the ha...
Rate-Distortion optimization can significantly improve encoder performance in MPEG-like video coding applications especially when it is applied to coding mode selection and motion...