We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
In this paper we propose an approach to address the old problem of identifying the feature conditions under which a gaming strategy can be effective. For doing this, we will build ...
Chad Hogg, Stephen Lee-Urban, Bryan Auslander, H&e...
This paper presents a cluster validation based document clustering algorithm, which is capable of identifying both important feature words and true model order (cluster number). I...
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the...
We recently proposed a method to find cluster structure in home videos based on statistical models of visual and temporal features of video segments and sequential binary Bayesian...
Daniel Gatica-Perez, Alexander C. Loui, Ming-Ting ...