Algorithmic advances in Riemannian geometry and applications : for machine learning, computer vision, statistics, and optimization (Record no. 30719)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220222b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319450254
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 516.373
Item number MIN
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Minh, Ha Quang ed.
245 ## - TITLE STATEMENT
Title Algorithmic advances in Riemannian geometry and applications : for machine learning, computer vision, statistics, and optimization
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2016
Place of publication, distribution, etc Cham :
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 208 p. ;
Other physical details ill., (some color),
Dimensions 25cm
365 ## - TRADE PRICE
Price amount 119.99
Price type code EUR
Unit of pricing 88.10
490 ## - SERIES STATEMENT
Series statement Advances in computer vision and pattern recognition
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using the mathematical machinery of Riemannian geometry. As demonstrated by all the chapters in the book, when the data is intrinsically non-Euclidean, the utilization of this geometrical information can lead to better algorithms that can capture more accurately the structures inherent in the data, leading ultimately to better empirical performance. This book is not intended to be an encyclopedic compilation of the applications of Riemannian geometry. Instead, it focuses on several important research directions that are currently actively pursued by researchers in the field. These include statistical modeling and analysis on manifolds, optimization on manifolds, Riemannian manifolds and kernel methods, and dictionary learning and sparse coding on manifolds. Examples of applications include novel algorithms for Monte Carlo sampling and Gaussian Mixture Model fitting, 3D brain image analysis, image classification, action recognition, and motion tracking.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics
Topical term or geographic name as entry element Machine learning
Topical term or geographic name as entry element Computer vision
Topical term or geographic name as entry element Computational Intelligence
Topical term or geographic name as entry element Mathematical Applications in Computer Science
Topical term or geographic name as entry element Probability and Statistics in Computer Science
Topical term or geographic name as entry element Affine-invariant distance
Topical term or geographic name as entry element Diffeomorphisms
Topical term or geographic name as entry element Frobenius norm
Topical term or geographic name as entry element Gaussian Kernel
Topical term or geographic name as entry element Hilbert-Schmidt operator
Topical term or geographic name as entry element Image classification
Topical term or geographic name as entry element Kotz-type distribution
Topical term or geographic name as entry element Log-Euclidean distance
Topical term or geographic name as entry element Lie algebra
Topical term or geographic name as entry element Positive definite Kernel
Topical term or geographic name as entry element Kernel Hilbert Space
Topical term or geographic name as entry element Riemannian manifold
Topical term or geographic name as entry element Shape analysis
Topical term or geographic name as entry element Symmetric positive definite (SPD) matrices
Topical term or geographic name as entry element Two-layer kernel machine
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Murino, Vittorio
Relator term ed.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Cost, normal purchase price Full call number Barcode Date last seen Koha item type
          DAIICT DAIICT 2022-02-21 10571.12 516.373 MIN 032821 2022-02-22 Books

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