An Invariant Variational Principle for Model-Based Interpolation of High Dimensional Clustered Data
نویسنده
چکیده
A self-consistent scheme based on the calculus of infinitesimal transformations that describes model based interpolation (MBI hereafter) of high dimensional data, constrained to lie on a nonlinear manifold, is expressed as a dynamical system. The variational formulation derived for a single cluster is extended to the case of finite mixture models (FMM hereafter). The suggested formulation is shown to be qualitatively dissimilar properties, and exhibits greater computational efficiency, as compared with a scheme derived using “classical” variational calculus.
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