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Algorithmic Advances in Riemannian Geometry and Applications

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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 1: Bayesian Statistical Shape Analysis on the Manifold of Diffeomorphisms
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