

Information Geometry and its Applications III
Abstract Raymond Streater
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Raymond Streater (King's College London, United Kingdom)
Tuesday, August 03, 2010, room Hörsaal 1
Relation between Jaynes estimation and Fisher information
Jaynes suggested that given random variables of unknown distribution, and measurements of them, then the best estimate for their joint distribution is given by maximising the entropy of all states, under the condition that they predict that the mean of each, in a distribution, be its exact mean. We show that this can be proved to be the best estimate, in that the scores,
have the least joint variance under this condition. The result is extended to quantum mechanics: the estimation of n self-adjoint quadratic forms that are Kato-small relative to a given positive self-adjoint operator.
Date and Location
August 02 - 06, 2010
University of Leipzig
Augustusplatz
04103 Leipzig
Germany
Scientific Organizers
Nihat AyMax Planck Institute for Mathematics in the Sciences
Information Theory of Cognitive Systems Group
Germany
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Paolo Gibilisco
Università degli Studi di Roma "Tor Vergata"
Facoltà di Economia
Italy
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František Matúš
Academy of Sciences of the Czech Republic
Institute of Information Theory and Automation
Czech Republic
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Scientific Committee
Shun-ichi Amari
RIKEN
Brain Science Institute, Mathematical Neuroscience Laboratory
Japan
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Imre Csiszár
Hungarian Academy of Sciences
Alfréd Rényi Institute of Mathematics
Hungary
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Dénes Petz
Budapest University of Technology and Economics
Department for Mathematical Analysis
Hungary
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Giovanni Pistone
Collegio Carlo Alberto, Moncalieri
Italy
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Administrative Contact
Antje Vandenberg
Max Planck Institute for Mathematics in the Sciences
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Phone: (++49)-(0)341-9959-552
Fax: (++49)-(0)341-9959-555