Sparsity and Geometry Preserving Graph Embedding for Dimensionality Reduction

Sparsity and Geometry Preserving Graph Embedding for Dimensionality Reduction

Graph embedding is a very useful dimensionality reduction technique in pattern recognition. In this paper, we develop a novel discriminative dimensionality reduction technique entitled sparsity and geometry preserving graph embedding (SGPGE). SGPGE can not only capture the sparse reconstructive rela...

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Bibliographic Details
Main Authors: Jianping Gou, Zhang Yi, David Zhang, Yongzhao Zhan, Xiangjun Shen, Lan Du
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Dimensionality reduction
graph embedding
sparse representation
sparsity and geometry preserving scatter
pattern recognition
Online Access:https://ieeexplore.ieee.org/document/8552351/

Internet

https://ieeexplore.ieee.org/document/8552351/

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