Probability-generating function kernels for spherical data
Abstract
The class of probability-generating function (PGF) kernels is introduced, which consists of kernels supported on the unit hypersphere, for the purposes of spherical data analysis. PGF kernels generalize RBF kernels in the context of spherical data. The properties of PGF kernels are studied. A semi-parametric learning algorithm is introduced to enable the use of PGF kernels with spherical data.
Type
Publication
In International Conference on Artificial Neural Networks (ICANN)
