Matrix Information Geometry

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Publisher : Springer Science & Business Media
ISBN 13 : 3642302327
Total Pages : 454 pages
Book Rating : 4.29/5 ( download)

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Book Synopsis Matrix Information Geometry by : Frank Nielsen

Download or read book Matrix Information Geometry written by Frank Nielsen and published by Springer Science & Business Media. This book was released on 2012-08-07 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering. The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and Applications in Cognitive systems, in particular Data Mining.

Information Geometry

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Publisher : MDPI
ISBN 13 : 3038976326
Total Pages : 355 pages
Book Rating : 4.25/5 ( download)

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Book Synopsis Information Geometry by : Geert Verdoolaege

Download or read book Information Geometry written by Geert Verdoolaege and published by MDPI. This book was released on 2019-04-04 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Special Issue of the journal Entropy, titled “Information Geometry I”, contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience.

Information Geometry and Its Applications

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Publisher : Springer
ISBN 13 : 4431559787
Total Pages : 378 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Information Geometry and Its Applications by : Shun-ichi Amari

Download or read book Information Geometry and Its Applications written by Shun-ichi Amari and published by Springer. This book was released on 2016-02-02 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive book on information geometry, written by the founder of the field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide range of applications, covering information science, engineering, and neuroscience. It consists of four parts, which on the whole can be read independently. A manifold with a divergence function is first introduced, leading directly to dualistic structure, the heart of information geometry. This part (Part I) can be apprehended without any knowledge of differential geometry. An intuitive explanation of modern differential geometry then follows in Part II, although the book is for the most part understandable without modern differential geometry. Information geometry of statistical inference, including time series analysis and semiparametric estimation (the Neyman–Scott problem), is demonstrated concisely in Part III. Applications addressed in Part IV include hot current topics in machine learning, signal processing, optimization, and neural networks. The book is interdisciplinary, connecting mathematics, information sciences, physics, and neurosciences, inviting readers to a new world of information and geometry. This book is highly recommended to graduate students and researchers who seek new mathematical methods and tools useful in their own fields.

Methods of Information Geometry

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Publisher : American Mathematical Soc.
ISBN 13 : 9780821843024
Total Pages : 220 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis Methods of Information Geometry by : Shun-ichi Amari

Download or read book Methods of Information Geometry written by Shun-ichi Amari and published by American Mathematical Soc.. This book was released on 2000 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information geometry provides the mathematical sciences with a fresh framework of analysis. This book presents a comprehensive introduction to the mathematical foundation of information geometry. It provides an overview of many areas of applications, such as statistics, linear systems, information theory, quantum mechanics, and convex analysis.

Geometric Structures of Information

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Publisher : Springer
ISBN 13 : 3030025209
Total Pages : 392 pages
Book Rating : 4.05/5 ( download)

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Book Synopsis Geometric Structures of Information by : Frank Nielsen

Download or read book Geometric Structures of Information written by Frank Nielsen and published by Springer. This book was released on 2018-11-19 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Information Geometry

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Publisher : Springer
ISBN 13 : 3319564781
Total Pages : 407 pages
Book Rating : 4.84/5 ( download)

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Book Synopsis Information Geometry by : Nihat Ay

Download or read book Information Geometry written by Nihat Ay and published by Springer. This book was released on 2017-08-25 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a comprehensive introduction and a novel mathematical foundation of the field of information geometry with complete proofs and detailed background material on measure theory, Riemannian geometry and Banach space theory. Parametrised measure models are defined as fundamental geometric objects, which can be both finite or infinite dimensional. Based on these models, canonical tensor fields are introduced and further studied, including the Fisher metric and the Amari-Chentsov tensor, and embeddings of statistical manifolds are investigated. This novel foundation then leads to application highlights, such as generalizations and extensions of the classical uniqueness result of Chentsov or the Cramér-Rao inequality. Additionally, several new application fields of information geometry are highlighted, for instance hierarchical and graphical models, complexity theory, population genetics, or Markov Chain Monte Carlo. The book will be of interest to mathematicians who are interested in geometry, information theory, or the foundations of statistics, to statisticians as well as to scientists interested in the mathematical foundations of complex systems.

Matrix Information Geometry

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Publisher : Springer
ISBN 13 : 9783642302336
Total Pages : 456 pages
Book Rating : 4.35/5 ( download)

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Book Synopsis Matrix Information Geometry by : Frank Nielsen

Download or read book Matrix Information Geometry written by Frank Nielsen and published by Springer. This book was released on 2012-08-04 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering. The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and Applications in Cognitive systems, in particular Data Mining.

Matrices and Graphs in Geometry

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Publisher : Cambridge University Press
ISBN 13 : 0521461936
Total Pages : 206 pages
Book Rating : 4.31/5 ( download)

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Book Synopsis Matrices and Graphs in Geometry by : Miroslav Fiedler

Download or read book Matrices and Graphs in Geometry written by Miroslav Fiedler and published by Cambridge University Press. This book was released on 2011-02-03 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrates the close relationship between matrix theory and elementary Euclidean geometry, with emphasis on using simple graph-theoretical notions.

Geometric Science of Information

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Publisher : Springer Nature
ISBN 13 : 3030802094
Total Pages : 929 pages
Book Rating : 4.97/5 ( download)

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Book Synopsis Geometric Science of Information by : Frank Nielsen

Download or read book Geometric Science of Information written by Frank Nielsen and published by Springer Nature. This book was released on 2021-07-14 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021. The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.

Optimization Algorithms on Matrix Manifolds

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Publisher : Princeton University Press
ISBN 13 : 9781400830244
Total Pages : 240 pages
Book Rating : 4.49/5 ( download)

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Book Synopsis Optimization Algorithms on Matrix Manifolds by : P.-A. Absil

Download or read book Optimization Algorithms on Matrix Manifolds written by P.-A. Absil and published by Princeton University Press. This book was released on 2009-04-11 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms. It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction--illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development. In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis. It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists.