Probabilistic Dimensional Reduction with Gaussian Process...Google Tech Talks February 12, 2007 ABSTRACT Density modelling in high dimensions is a very difficult problem. Traditional approaches, such as mixtures of Gaussians, typically fail to capture the structure of data sets in high dimensional spaces. In this talk we will argue that for many data sets of interest, the data can be represented as a lower dimensional manifold immersed in the higher dime
