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(Neural Computation. 2005;17:503-513.)
© 2005 The MIT Press

Note

Maximum Likelihood Topographic Map Formation

Marc M. Van Hulle

marc{at}neuro.kuleuven.ac.be, K.U.Leuven, Laboratorium voor Neuro- en Psychofysiologie, B-3000 Leuven, Belgium

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.




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M. M. V. Hulle
Differential Log Likelihood for Evaluating and Learning Gaussian Mixtures
Neural Comput., February 1, 2005; 18(2): 430 - 445.
[Abstract] [Full Text] [PDF]


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