Graph decomposition lemmas and their role in metric embedding methods

Yair Bartal

doi:10.1007/978-3-540-30140-0_10

Graph decomposition lemmas and their role in metric embedding methods

Yair Bartal^*

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

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

47 Scopus citations

Abstract

We present basic graph decomposition lemmas and show how they apply as key ingredients in the probabilistic embedding theorem stating that every n point metric space probabilistically embeds in ultrametries with distortion O(log n) and in the proof of a similar bound for the spreading metrics paradigm in undirected graphs. This provides a unified framework for these metric methods which have numerous algorithmic applications.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Susanne Albers, Tomasz Radzik
Publisher	Springer Verlag
Pages	89-97
Number of pages	9
ISBN (Print)	3540230254, 9783540230250
DOIs	https://doi.org/10.1007/978-3-540-30140-0_10
State	Published - 2004

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3221
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-540-30140-0_10

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Bartal, Y. (2004). Graph decomposition lemmas and their role in metric embedding methods. In S. Albers, & T. Radzik (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 89-97). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3221). Springer Verlag. https://doi.org/10.1007/978-3-540-30140-0_10

Bartal, Yair. / Graph decomposition lemmas and their role in metric embedding methods. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Susanne Albers ; Tomasz Radzik. Springer Verlag, 2004. pp. 89-97 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Bartal, Y 2004, Graph decomposition lemmas and their role in metric embedding methods. in S Albers & T Radzik (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3221, Springer Verlag, pp. 89-97. https://doi.org/10.1007/978-3-540-30140-0_10

Graph decomposition lemmas and their role in metric embedding methods. / Bartal, Yair.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Susanne Albers; Tomasz Radzik. Springer Verlag, 2004. p. 89-97 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3221).

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

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Bartal Y. Graph decomposition lemmas and their role in metric embedding methods. In Albers S, Radzik T, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 89-97. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30140-0_10

Graph decomposition lemmas and their role in metric embedding methods

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