Manifold Learning Based on Straight-Like Geodesics and Local Coordinates

IEEE Transactions on Neural Networks and Learning Systems(2021)

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摘要
In this article, a manifold learning algorithm based on straight-like geodesics and local coordinates is proposed, called SGLC-ML for short. The contribution and innovation of SGLC-ML lie in that; first, SGLC-ML divides the manifold data into a number of straight-like geodesics, instead of a number of local areas like many manifold learning algorithms do. Figuratively speaking, SGLC-ML covers mani...
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关键词
Manifolds,Dimensionality reduction,Learning systems,Technological innovation,Indexes,Education,Weaving
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