Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
One of the objectives of this paper is to verify whether it is possible to extract meaningful related tags from a limited set of tagged resources and from resources tagged by only ...
Abstract. This paper presents an online learning algorithm for appearancebased gaze estimation that allows free head movement in a casual desktop environment. Our method avoids the...
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...