Issue No. 11 - November (2000 vol. 22)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.888716
<p><b>Abstract</b>—Gradient-quadratic and fixed-point iteration algorithms and appropriate values for their control parameters are derived for finding all modes of a Gaussian mixture, a problem with applications in clustering and regression. The significance of the modes found is quantified locally by Hessian-based error bars and globally by the entropy as sparseness measure.</p>
Gaussian mixtures, maximization algorithms, mode finding, bump finding, error bars, sparseness.
M. &. Carreira-Perpiñán, "Mode-Finding for Mixtures of Gaussian Distributions," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 22, no. , pp. 1318-1323, 2000.