"This course will consist of a number of major sections. The first will be a short review of some preliminary material, including asymptotics, summations, and recurrences and ...
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Several studies have demonstrated the effectiveness of the wavelet decomposition as a tool for reducing large amounts of data down to compact wavelet synopses that can be used to ...
Abstract--We present an explicit formula for B-spline convolution kernels; these are defined as the convolution of several B-splines of variable widths and degrees . We apply our r...
Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate max...