Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
Precise automated video search is gaining in importance as the amount of multimedia information is increasing at exponential rates. One of the drawbacks that make video retrieval ...
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
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...