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Minh, Hà Quang

Algorithmic Advances in Riemannian Geometry and Applications

Minh, Hà Quang - Algorithmic Advances in Riemannian Geometry and Applications, ebook

130,70€

Ebook, PDF with Adobe DRM
ISBN: 9783319450261
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Table of contents

1. Bayesian Statistical Shape Analysis on the Manifold of Diffeomorphisms
Miaomiao Zhang, P. Thomas Fletcher

2. Sampling Constrained Probability Distributions Using Spherical Augmentation
Shiwei Lan, Babak Shahbaba

3. Geometric Optimization in Machine Learning
Suvrit Sra, Reshad Hosseini

4. Positive Definite Matrices:
Data
Representation
and Applications to Computer Vision
Anoop Cherian, Suvrit Sra

5. From Covariance Matrices to Covariance Operators: Data Representation from Finite to Infinite-Dimensional Settings
Hà Quang Minh, Vittorio Murino

6. Dictionary Learning on Grassmann Manifolds
Mehrtash Harandi, Richard Hartley, Mathieu Salzmann, Jochen Trumpf

7. Regression on Lie Groups and Its Application to Affine Motion Tracking
Fatih Porikli

8. An Elastic Riemannian Framework for Shape Analysis
of Curves and Tree-Like Structures
Adam Duncan, Zhengwu Zhang, Anuj Srivastava

Keywords: Computer Science, Pattern Recognition, Computational Intelligence, Statistics and Computing/Statistics Programs, Mathematical Applications in Computer Science, Artificial Intelligence (incl. Robotics), Probability and Statistics in Computer Science

Editor
 
Publisher
Springer
Publication year
2016
Language
en
Edition
1
Series
Advances in Computer Vision and Pattern Recognition
Category
Information Technology, Telecommunications
Format
Ebook
eISBN (PDF)
9783319450261
Printed ISBN
978-3-319-45025-4

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