Action recognition is an important but challenging problem in video analytics with a number of solutions proposed to date. However, even if a reliable model for action representat...
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
The paper reconsiders the autoregressive aided periodogram bootstrap (AAPB) which has been suggested in Kreiß and Paparoditis (2003). Their idea was to combine a time domain param...