By Hà Quang Minh,Vittorio Murino
This ebook offers a range of the newest algorithmic advances in Riemannian geometry within the context of desktop studying, records, optimization, computer vision, and similar fields. The unifying subject matter of the various chapters within the book is the exploitation of the geometry of knowledge utilizing the mathematical equipment of Riemannian geometry. As proven by way of all of the chapters within the ebook, while the data is intrinsically non-Euclidean, the usage of this geometrical info can lead to greater algorithms that may trap extra competently the buildings inherent in the data, best finally to higher empirical functionality. This publication isn't really meant to be an encyclopedic compilation of the purposes of Riemannian geometry. as a substitute, it focuses on a number of very important learn instructions which are presently 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 purposes comprise novel algorithms for Monte Carlo sampling and Gaussian combination version becoming, 3D mind picture analysis,image category, motion attractiveness, and movement tracking.
Read or Download Algorithmic Advances in Riemannian Geometry and Applications: For Machine Learning, Computer Vision, Statistics, and Optimization (Advances in Computer Vision and Pattern Recognition) PDF
Best mathematical & statistical books
Over the last years, clinical computing has develop into an immense study department situated among utilized arithmetic and technologies and engineering. hugely effective numerical equipment are according to adaptive equipment, larger order discretizations, speedy linear and non-linear iterative solvers, multi-level algorithms, and so forth.
Images are nice for exploring info, yet how can they be used for taking a look at the massive datasets which are standard to-day? This booklet indicates tips to examine methods of visualizing huge datasets, even if huge in numbers of instances or huge in numbers of variables or huge in either. facts visualization comes in handy for facts cleansing, exploring information, picking out developments and clusters, recognizing neighborhood styles, comparing modeling output, and proposing effects.
Up-to-date to mirror SAS nine. 2, A guide of Statistical Analyses utilizing SAS, 3rd version maintains to supply a simple description of the way to behavior a number of statistical analyses utilizing SAS. each one bankruptcy exhibits tips on how to use SAS for a selected kind of research. The authors conceal inference, research of variance, regression, generalized linear versions, longitudinal info, survival research, crucial elements research, issue research, cluster research, discriminant functionality research, and correspondence research.
Networks have permeated way of life via daily realities just like the net, social networks, and viral advertising and marketing. As such, community research is a vital development quarter within the quantitative sciences, with roots in social community research going again to the Thirties and graph conception going again centuries.
- Mastering Python for Finance
- Recent Advances in Natural Computing: Selected Results from the IWNC 7 Symposium (Mathematics for Industry)
- Statistical Analysis with Excel For Dummies
- A First Course in Bayesian Statistical Methods (Springer Texts in Statistics)
Additional resources 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