By Hà Quang Minh,Vittorio Murino
This booklet provides a range of the latest algorithmic advances in Riemannian geometry within the context of computing device studying, statistics, optimization, computer vision, and comparable fields. The unifying subject of the several chapters within the book is the exploitation of the geometry of information utilizing the mathematical equipment of Riemannian geometry. As tested via the entire chapters within the e-book, while the data is intrinsically non-Euclidean, the usage of this geometrical details can lead to larger algorithms which may seize extra adequately the constructions inherent in the data, best finally to raised empirical functionality. This publication isn't really meant to be an encyclopedic compilation of the functions of Riemannian geometry. as an alternative, it focuses on numerous vital study instructions which are at the moment actively pursued by researchers within the box. those comprise statistical modeling and research on manifolds,optimization on manifolds, Riemannian manifolds and kernel equipment, and dictionary learning and sparse coding on manifolds. Examples of functions contain novel algorithms for Monte Carlo sampling and Gaussian combination version becoming, 3D mind photo analysis,image type, motion acceptance, and movement tracking.
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Extra info for Algorithmic Advances in Riemannian Geometry and Applications: For Machine Learning, Computer Vision, Statistics, and Optimization (Advances in Computer Vision and Pattern Recognition)
Algorithmic Advances in Riemannian Geometry and Applications: For Machine Learning, Computer Vision, Statistics, and Optimization (Advances in Computer Vision and Pattern Recognition) by Hà Quang Minh,Vittorio Murino