Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Skeleton Decomposition Analysis for Subspace Clustering
Date
2016-12-08
Author
Sekmen, Ali
Aldroubi, Akram
Koku, Ahmet Buğra
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
3
views
0
downloads
This paper provides a comprehensive analysis of skeleton decomposition used for segmentation of data W = [w(1) center dot center dot center dot w(N)] subset of R-D drawn from a union u = U-i=1(M) S-i of linearly independent subspaces {Si}(M)(i=1) of dimensionsof {di}(M)(i=1). Our previous work developed a generalized theoretical framework for computing similarity matrices by matrix factorization. Skeleton decomposition is a special case of this general theory. First, a square sub-matrix A is an element of R-rxr of W with the same rank r as W is found. Then, the corresponding row restriction R of W is constructed. This leads to P= A(-1)R and corresponding similarity matrix SW = ((PP)-P-T)(dmax), where d(max) is the maximum subspace dimension. Since most of the data matrices are low-rank in many subspace segmentation problems, this is computationally efficient compared to the other constructions of similarity matrices. It is also shown (with some limitations) that center-of-mass based sorting of data columns in SW can be used to quickly assess clustering performance while algorithm development in both noisy or noise-free cases.
Subject Keywords
Subspace segmentation
,
Union of subspaces
,
Data clustering
,
Similarity matrix
,
Skeleton decomposition
URI
https://hdl.handle.net/11511/41679
DOI
https://doi.org/10.1109/bigdata.2016.7840802
Collections
Department of Mechanical Engineering, Conference / Seminar