Abstract. In this paper a new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is...
In the paper the idea is presented that emotions are the result of a high dimensional optimization process happening in the unconscious mapped onto the low dimensional conscious. I...
Range searches in metric spaces can be very di cult if the space is \high dimensional", i.e. when the histogram of distances has a large mean and a small variance. The so-cal...
A geometric framework for image scale space, enhancement, and segmentation is presented. We consider intensity images as surfaces in the (x I) space. The image is thereby a 2D surf...
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...