FINE: Fisher Information Nonparametric Embedding

We consider the problems of clustering, classification, and visualization of high-dimensional data when no straightforward Euclidean representation exists. In this paper, we propose using the properties of information geometry and statistical manifolds in order to define similarities between data se...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2009-11, Vol.31 (11), p.2093-2098
Hauptverfasser:	Carter, K.M., Raich, R., Finn, W.G., Hero, A.O.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analogies Applied sciences Approximation Artificial Intelligence Classification Cluster Analysis Computer science control theory systems Computer Simulation Data processing. List processing. Character string processing Data visualization Databases, Factual dimensionality reduction Exact sciences and technology Face recognition Image reconstruction Image segmentation Image texture analysis Information geometry Information retrieval Information Storage and Retrieval - methods Learning Manifolds Memory organisation. Data processing Models, Theoretical multidimensional scaling Multidimensional systems Parametrization Pattern analysis Pattern Recognition, Automated - methods Probability density function Representations Software Solid modeling statistical manifold User-Computer Interface
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