Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
: This report introduces a geometrical constraint kernel for handling the location in space and time of polymorphic k-dimensional objects subject to various geometrical and time co...
Nicolas Beldiceanu, Mats Carlsson, Emmanuel Poder,...
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...