In this paper, we propose a novel nonparametric modeling technique, namely Space Kernel Analysis (SKA), as a result of the definition of the space kernel. We analyze the uncertai...
We investigate the asymptotic properties of a recursive kernel density estimator associated with the driven noise of a linear regression in adaptive tracking. We provide an almost ...
We address the problem of classification of EEG recordings for the detection of epileptic seizures. We assume that the EEG measurements can be described by a low dimensional manif...
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...