We extend the standard mixture of linear regressions model by allowing mixing proportions to be modeled nonparametrically as a function of the predictors. This framework allows fo...
This study presents a new evolutionary network minimization (ENM) algorithm. Neurocontroller minimization is beneficial for finding small parsimonious networks that permit a better...
This paper is concerned with the selection of a generative model for supervised classification. Classical criteria for model selection assess the fit of a model rather than its abi...
Constrained parameterization is an effective way to establish texture coordinates between a 3D surface and an existing image or photograph. A known drawback to constrained paramet...
Yu-Wing Tai, Michael S. Brown, Chi-Keung Tang, Heu...
This paper introduces a new approach to describe the spread of research topics across disciplines using epidemic models. The approach is based on applying individual-based models ...
Istvan Z. Kiss, Mark Broom, Paul G. Craze, Ismael ...