title: Clustering via kernel decomposition.
abstract: Spectral clustering methods were proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this letter, the affinity matrix is created from the elements of a nonparametric density estimator and then decomposed to obtain posterior probabilities of class membership. Hyperparameters are selected using standard cross-validation methods.
authors.forename: A
authors.initials: A
authors.lastname: Szymkowiak-Have
authors.forename: Mark A
authors.initials: MA
authors.lastname: Girolami
authors.forename: Jan
authors.initials: J
authors.lastname: Larsen