Geometric Structures of Information / edited by Frank Nielsen.
Contributor(s): SpringerLink (Online service)
| Nielsen, Frank., editor literario
Series: (Engineering (Springer-11647)); (Signals and Communication Technology, 1860-4862).Publisher: Cham : Imprint: Springer, 2019Description: 1 recurso en línea (VIII, 392 páginas) : 49 ilustraciones, 36 ilustraciones a color.ISBN: 9783030025205.Subject: Estadística matemática
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA276.23 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks24062631 |
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| QA276 .P46 2014 EB Fundamentos de estadística | QA276.2 2014 EB Ejercicios resueltos de técnicas cuantitativas para la inferencia | QA276.2 .S73 Statista | QA276.23 2019 EB Geometric Structures of Information | QA276.4 ES Computational Statistics | QA276.4 ES Statistics and Computing | QA276.4 .Y245 2011 EB Visualize this : the FlowingData guide to design, visualization, and statistics |
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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