Algorithmic Advances in Riemannian Geometry and Applications
-15%
portes grátis
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Riemannian Geometry;Machine Learning;Optimization;Statistics;Computer Vision
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
