  Probability-generating function (PGF) kernels are introduced, which
constitute a class 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.
