Algorithmic Advances in Riemannian Geometry and Applications

Algorithmic Advances in Riemannian Geometry and Applications

For Machine Learning, Computer Vision, Statistics, and Optimization

Minh, Ha Quang; Murino, Vittorio

Springer International Publishing AG

06/2018

208

Mole

Inglês

9783319831909

15 a 20 dias

3868

Descrição não disponível.
Introduction.- Bayesian Statistical Shape Analysis on the Manifold of Diffeomorphisms.- Sampling Constrained Probability Distributions using Spherical Augmentation.- Geometric Optimization in Machine Learning.- Positive Definite Matrices: Data Representation and Applications to Computer Vision.- From Covariance Matrices to Covariance Operators: Data Representation from Finite to Infinite-Dimensional Settings.- Dictionary Learning on Grassmann Manifolds.- Regression on Lie Groups and its Application to Affine Motion Tracking.- An Elastic Riemannian Framework for Shape Analysis of Curves and Tree-Like Structures.
Riemannian Geometry;Machine Learning;Optimization;Statistics;Computer Vision