On spectral clustering: Analysis and an algorithm

Andrew Y. Ng; Michael I. Jordan; Yair Weiss

On spectral clustering: Analysis and an algorithm

Andrew Y. Ng, Michael I. Jordan, Yair Weiss

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4214 Scopus citations

Abstract

Despite many empirical successes of spectral clustering methods- Algorithms that cluster points using eigenvectors of matrices derived from the data-there are several unresolved issues. First, there are a wide variety of algorithms that use the eigenvectors in slightly different ways. Second, many of these algorithms have 110 proof that they will actually compute a reasonable clustering. T11 this paper, we present a simple spectral clustering algorithm that can be implemented using a few lines of Matlab. Using tools from matrix perturbation theory, we analyze the algorithm, and give conditions under which it can be expected to do well. We also show surprisingly good experimental results 011 a number of challenging clustering problems.

Original language	English
Title of host publication	Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001
Publisher	Neural information processing systems foundation
ISBN (Print)	0262042088, 9780262042086
State	Published - 2002
Event	15th Annual Neural Information Processing Systems Conference, NIPS 2001 - Vancouver, BC, Canada Duration: 3 Dec 2001 → 8 Dec 2001

Publication series

Name	Advances in Neural Information Processing Systems
ISSN (Print)	1049-5258

Conference

Conference	15th Annual Neural Information Processing Systems Conference, NIPS 2001
Country/Territory	Canada
City	Vancouver, BC
Period	3/12/01 → 8/12/01

Cite this

@inproceedings{d69168735a23434b90720e92b752c533,

title = "On spectral clustering: Analysis and an algorithm",

abstract = "Despite many empirical successes of spectral clustering methods- Algorithms that cluster points using eigenvectors of matrices derived from the data-there are several unresolved issues. First, there are a wide variety of algorithms that use the eigenvectors in slightly different ways. Second, many of these algorithms have 110 proof that they will actually compute a reasonable clustering. T11 this paper, we present a simple spectral clustering algorithm that can be implemented using a few lines of Matlab. Using tools from matrix perturbation theory, we analyze the algorithm, and give conditions under which it can be expected to do well. We also show surprisingly good experimental results 011 a number of challenging clustering problems.",

author = "Ng, {Andrew Y.} and Jordan, {Michael I.} and Yair Weiss",

year = "2002",

language = "אנגלית",

isbn = "0262042088",

series = "Advances in Neural Information Processing Systems",

publisher = "Neural information processing systems foundation",

booktitle = "Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001",

note = "15th Annual Neural Information Processing Systems Conference, NIPS 2001 ; Conference date: 03-12-2001 Through 08-12-2001",

}

Ng, AY, Jordan, MI & Weiss, Y 2002, On spectral clustering: Analysis and an algorithm. in Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001. Advances in Neural Information Processing Systems, Neural information processing systems foundation, 15th Annual Neural Information Processing Systems Conference, NIPS 2001, Vancouver, BC, Canada, 3/12/01.

On spectral clustering: Analysis and an algorithm. / Ng, Andrew Y.; Jordan, Michael I.; Weiss, Yair.
Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001. Neural information processing systems foundation, 2002. (Advances in Neural Information Processing Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - On spectral clustering

T2 - 15th Annual Neural Information Processing Systems Conference, NIPS 2001

AU - Ng, Andrew Y.

AU - Jordan, Michael I.

AU - Weiss, Yair

PY - 2002

Y1 - 2002

N2 - Despite many empirical successes of spectral clustering methods- Algorithms that cluster points using eigenvectors of matrices derived from the data-there are several unresolved issues. First, there are a wide variety of algorithms that use the eigenvectors in slightly different ways. Second, many of these algorithms have 110 proof that they will actually compute a reasonable clustering. T11 this paper, we present a simple spectral clustering algorithm that can be implemented using a few lines of Matlab. Using tools from matrix perturbation theory, we analyze the algorithm, and give conditions under which it can be expected to do well. We also show surprisingly good experimental results 011 a number of challenging clustering problems.

AB - Despite many empirical successes of spectral clustering methods- Algorithms that cluster points using eigenvectors of matrices derived from the data-there are several unresolved issues. First, there are a wide variety of algorithms that use the eigenvectors in slightly different ways. Second, many of these algorithms have 110 proof that they will actually compute a reasonable clustering. T11 this paper, we present a simple spectral clustering algorithm that can be implemented using a few lines of Matlab. Using tools from matrix perturbation theory, we analyze the algorithm, and give conditions under which it can be expected to do well. We also show surprisingly good experimental results 011 a number of challenging clustering problems.

UR - http://www.scopus.com/inward/record.url?scp=84899013108&partnerID=8YFLogxK

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:84899013108

SN - 0262042088

SN - 9780262042086

T3 - Advances in Neural Information Processing Systems

BT - Advances in Neural Information Processing Systems 14 - Proceedings of the 2001 Conference, NIPS 2001

PB - Neural information processing systems foundation

Y2 - 3 December 2001 through 8 December 2001

ER -

On spectral clustering: Analysis and an algorithm

Abstract

Publication series

Conference

Other files and links

Fingerprint

Cite this