We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to i...
Abstract. We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The out...
—We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for ...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...