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Geometric structures of information

Nielsen, Frank.

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Geometric structures of information

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Geometric structures of information/ edited by Frank Nielsen.
其他作者:	Nielsen, Frank.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	viii, 392 p. :ill., digital ;24 cm.
內容註:	Rho-Tau Embedding of Statistical Models -- A class of non-parametric deformed exponential statistical models -- Statistical Manifolds Admitting Torsion and Partially Flat Spaces -- Conformal attening on the probability simplex and its applications to Voronoi partitions and centroids Atsumi Ohara -- Monte Carlo Information-Geometric Structures -- Information geometry in portfolio theory -- Generalising Frailty Assumptions in Survival Analysis: a Geometric Approach -- Some Universal Insights on Divergences for Statistics, Machine Learning and Articial Intelligence -- Information-Theoretic Matrix Inequalities and Diusion Processes on Unimodular Lie Groups.
Contained By:	Springer eBooks
標題:	Geometrical models in statistics. -
電子資源:	https://doi.org/10.1007/978-3-030-02520-5
ISBN:	9783030025205

Geometric structures of information
Geometric structures of information[electronic resource] /edited by Frank Nielsen. - Cham :Springer International Publishing :2019. - viii, 392 p. :ill., digital ;24 cm. - Signals and communication technology,1860-4862. - Signals and communication technology..

Rho-Tau Embedding of Statistical Models -- A class of non-parametric deformed exponential statistical models -- Statistical Manifolds Admitting Torsion and Partially Flat Spaces -- Conformal attening on the probability simplex and its applications to Voronoi partitions and centroids Atsumi Ohara -- Monte Carlo Information-Geometric Structures -- Information geometry in portfolio theory -- Generalising Frailty Assumptions in Survival Analysis: a Geometric Approach -- Some Universal Insights on Divergences for Statistics, Machine Learning and Articial Intelligence -- Information-Theoretic Matrix Inequalities and Diusion Processes on Unimodular Lie Groups.

This book focuses on information geometry manifolds of structured data/information and their advanced applications featuring new and fruitful interactions between several branches of science: information science, mathematics and physics. It addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds, relational and discrete metric spaces, computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing.The book collects the most important contributions to the conference GSI'2017 - Geometric Science of Information.

ISBN: 9783030025205

Standard No.: 10.1007/978-3-030-02520-5doiSubjects--Topical Terms:

3252266
Geometrical models in statistics.

LC Class. No.: QA276.23 / .G466 2019

Dewey Class. No.: 519.5

Geometric structures of information
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505 0 $a Rho-Tau Embedding of Statistical Models -- A class of non-parametric deformed exponential statistical models -- Statistical Manifolds Admitting Torsion and Partially Flat Spaces -- Conformal attening on the probability simplex and its applications to Voronoi partitions and centroids Atsumi Ohara -- Monte Carlo Information-Geometric Structures -- Information geometry in portfolio theory -- Generalising Frailty Assumptions in Survival Analysis: a Geometric Approach -- Some Universal Insights on Divergences for Statistics, Machine Learning and Articial Intelligence -- Information-Theoretic Matrix Inequalities and Diusion Processes on Unimodular Lie Groups.
520 $a This book focuses on information geometry manifolds of structured data/information and their advanced applications featuring new and fruitful interactions between several branches of science: information science, mathematics and physics. It addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds, relational and discrete metric spaces, computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing.The book collects the most important contributions to the conference GSI'2017 - Geometric Science of Information.
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