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Algorithmic Advances in Riemannian Geometry and Applications

Overview of attention for book
Cover of 'Algorithmic Advances in Riemannian Geometry and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Bayesian Statistical Shape Analysis on the Manifold of Diffeomorphisms
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    Chapter 2 Sampling Constrained Probability Distributions Using Spherical Augmentation
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    Chapter 3 Geometric Optimization in Machine Learning
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    Chapter 4 Positive Definite Matrices: Data Representation and Applications to Computer Vision
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    Chapter 5 From Covariance Matrices to Covariance Operators: Data Representation from Finite to Infinite-Dimensional Settings
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    Chapter 6 Dictionary Learning on Grassmann Manifolds
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    Chapter 7 Regression on Lie Groups and Its Application to Affine Motion Tracking
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    Chapter 8 An Elastic Riemannian Framework for Shape Analysis of Curves and Tree-Like Structures
Attention for Chapter 6: Dictionary Learning on Grassmann Manifolds
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Chapter title
Dictionary Learning on Grassmann Manifolds
Chapter number 6
Book title
Algorithmic Advances in Riemannian Geometry and Applications
Published by
Springer International Publishing, October 2016
DOI 10.1007/978-3-319-45026-1_6
Book ISBNs
978-3-31-945025-4, 978-3-31-945026-1
Authors

Mehrtash Harandi, Richard Hartley, Mathieu Salzmann, Jochen Trumpf

Editors

Hà Quang Minh, Vittorio Murino

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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