Manifold Learning by Curved Cosine Mapping

In the field of pattern recognition, data analysis, and machine learning, data points are usually modeled as high-dimensional vectors. Due to the curse-of-dimensionality, it is non-trivial to efficiently process the orginal data directly. Given the unique properties of nonlinear dimensionality reduc...

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Bibliographic Details
Published in:	IEEE transactions on knowledge and data engineering 2017-10, Vol.29 (10), p.2236-2248
Main Authors:	Gu, Huamao, Wang, Xun, Chen, Xuewen, Deng, Shaoping, Shi, Jinqin
Format:	Article
Language:	English
Subjects:	Analytical models Bridges Computational modeling Data analysis Data models Data points dimensionality reduction Euclidean geometry Euclidean space law of cosines Learning systems Machine learning Manifolds Manifolds (mathematics) Manifold learning Mapping nearest neighbour graph Pattern analysis Pattern recognition pattern recognition Reduction Teaching methods
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