A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data.
Real-world data are frequently corrupted with both sparse error and noise.
Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption.
In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range.
An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix.
To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge.
The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix.
Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.
American Psychological Association (APA)
Sun, Yubao& Li, Zhi& Wu, Min. 2015. A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1074167
Modern Language Association (MLA)
Sun, Yubao…[et al.]. A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering. Mathematical Problems in Engineering No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1074167
American Medical Association (AMA)
Sun, Yubao& Li, Zhi& Wu, Min. A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1074167
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074167