The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Abstract. Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence ...
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
With the recent efforts made by computer vision researchers,
more and more types of features have been designed
to describe various aspects of visual characteristics.
Modeling s...
Liangliang Cao, Jiebo Luo, Feng Liang, Thomas S. H...