In this study, we investigate online Bayesian estimation of the measurement noise density of a given state space model using particle filters and Dirichlet process mixtures. Diri...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
A possible approach to bandwidth selection for difference-based variance estimators in the nonparametric regression is proposed. The approach is based on the crossvalidation-type ...
Abstract— A novel nonparametric paradigm to model identification has been recently proposed where, in place of postulating finite-dimensional models of the system transfer func...
Gianluigi Pillonetto, Alessandro Chiuso, Giuseppe ...
Abstract. This paper presents a novel approach to unsupervised texture segmentation that relies on a very general nonparametric statistical model of image neighborhoods. The method...