Linear Subspace and Manifold Learning via Extrinsic Geometry

Linear Subspace and Manifold Learning via Extrinsic Geometry

<p>In the last few decades, data analysis techniques have had to expand to handle large sets of data with complicated structure. This includes identifying low dimensional structure in high dimensional data, analyzing shape and image data, and learning from or classifying large corpora of text...

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Bibliographic Details
Main Author: St. Thomas, Brian Stephen
Other Authors: Mukherjee, Sayan
Published: 2015
Subjects:
Statistics
Theoretical mathematics
Applied mathematics
Admixture Modeling
Extrinsic Geometry
Kernel Regression
Mixture Modeling
Monotone Regression
Riemannian Manifolds
Online Access:http://hdl.handle.net/10161/10529

Internet

http://hdl.handle.net/10161/10529

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