Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
In this paper, we develop a system to classify the outputs of image segmentation algorithms as perceptually relevant or perceptually irrelevant with respect to human perception. T...
In this article we review some recent interactions between harmonic analysis and data compression. The story goes back of course to Shannon’s R(D) theory in the case of Gaussian...
David L. Donoho, Martin Vetterli, Ronald A. DeVore...
In this paper, we present a novel modeling method for synthesizing rough surfaces using discrete surface growth models. We employ a two-pass method. Initial point cluster data is ...
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...