CUR Decompositions, Similarity Matrices, and Subspace Clustering

CUR Decompositions, Similarity Matrices, and Subspace Clustering

A general framework for solving the subspace clustering problem using the CUR decomposition is presented. The CUR decomposition provides a natural way to construct similarity matrices for data that come from a union of unknown subspaces U=⋃Mi=1Si. The similarity matrices thus constructed give the ex...

Full description

Bibliographic Details
Main Authors: Akram Aldroubi, Keaton Hamm, Ahmet Bugra Koku, Ali Sekmen
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-01-01
Series:Frontiers in Applied Mathematics and Statistics
Subjects:
subspace clustering
similarity matrix
CUR decomposition
union of subspaces
data clustering
skeleton decomposition
Online Access:https://www.frontiersin.org/article/10.3389/fams.2018.00065/full

Internet

https://www.frontiersin.org/article/10.3389/fams.2018.00065/full

Similar Items