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Geometric Structures of Information [electronic resource] / edited by Frank Nielsen.

Contributor(s): Nielsen, Frank [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Signals and Communication Technology: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019.Description: VIII, 392 p. 49 illus., 36 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030025205.Subject(s): Telecommunication | Coding theory | Information theory | Global analysis (Mathematics) | Manifolds (Mathematics) | Communications Engineering, Networks | Coding and Information Theory | Global Analysis and Analysis on ManifoldsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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