By Hà Quang Minh,Vittorio Murino
This e-book provides a range of the newest algorithmic advances in Riemannian geometry within the context of laptop studying, statistics, optimization, computer vision, and comparable fields. The unifying topic of the several chapters within the book is the exploitation of the geometry of knowledge utilizing the mathematical equipment of Riemannian geometry. As established via all of the chapters within the ebook, 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, prime finally to raised empirical functionality. This publication isn't really meant to be an encyclopedic compilation of the purposes of Riemannian geometry. as an alternative, it focuses on numerous very important examine instructions which are at present 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 blend version becoming, 3D mind photo analysis,image category, motion attractiveness, and movement tracking.
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Additional 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