This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an a...
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
We study hierarchical classification in the general case when an instance could belong to more than one class node in the underlying taxonomy. Experiments done in previous work sh...