<inline-formula> <tex-math notation="LaTeX">${L_{2,1}}$ </tex-math></inline-formula>-Norm Discriminant Manifold Learning

<inline-formula> <tex-math notation="LaTeX">${L_{2,1}}$ </tex-math></inline-formula>-Norm Discriminant Manifold Learning

Recently, L<sub>1</sub>-norm-based robust discriminant feature extraction technique has been attracted much attention in dimensionality reduction and pattern recognition. However, it does not relate to the scatter matrix which well characterizes the geometric structure of data. In this p...

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Bibliographic Details
Main Authors: Yang Liu, Quanxue Gao, Xinbo Gao, Ling Shao
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">L</italic>₁-norm
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">L</italic>₂, ₁-norm
manifold learning
dimensionality reduction
Online Access:https://ieeexplore.ieee.org/document/8419246/

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https://ieeexplore.ieee.org/document/8419246/

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