Maximum likelihood topographic map formation.
We introduce a new unsupervised learning algorithm for kernel-based topographic map formation of heteroscedastic gaussian mixtures that allows for a unified account of distortion error (vector quantization), log-likelihood, and Kullback-Leibler divergence.
Van Hulle
Marc M
MM
K.U.Leuven, Laboratorium voor Neuro- en Psychofysiologie, B-3000 Leuven, Belgium. marc@neuro.kuleuven.ac.be
D000465:Algorithms; D001931:Brain Mapping; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology*; D016013:Likelihood Functions