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Approximation algorithms for embedding general metrics into trees
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Source Symposium on Discrete Algorithms archive
Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms table of contents
New Orleans, Louisiana
Pages: 512 - 521  
Year of Publication: 2007
ISBN:978-0-898716-24-5
Authors
Mihai Bǎdoiu  MIT Computer Science and Artificial Intelligence Laboratory; Cambridge, Massachusetts
Piotr Indyk  MIT Computer Science and Artificial Intelligence Laboratory; Cambridge, Massachusetts
Anastasios Sidiropoulos  MIT Computer Science and Artificial Intelligence Laboratory; Cambridge, Massachusetts
Sponsors
: SIAM Activity Group on Discrete Mathematics
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
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ABSTRACT

We consider the problem of embedding general metrics into trees. We give the first non-trivial approximation algorithm for minimizing the multiplicative distortion. Our algorithm produces an embedding with distortion (c log n)O(√log Δ), where c is the optimal distortion, and Δ is the spread of the metric (i.e. the ratio of the diameter over the minimum distance). We give an improved O(1)-approximation algorithm for the case where the input is the shortest path metric over an unweighted graph. Moreover, we show that by composing our approximation algorithm for embedding general metrics into trees, with the approximation algorithm of [BCIS05] for embedding trees into the line, we obtain an improved approximation algorithm for embedding general metrics into the line.

We also provide almost tight bounds for the relation between embedding into trees and embedding into spanning subtrees. We show that for any unweighted graph G, the ratio of the distortion required to embed G into a spanning subtree, over the distortion of an optimal tree embedding of G, is at most O(log n). We complement this bound by exhibiting a family of graphs for which the ratio is Ω(log n/log log n).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Mihai Bǎdoiu: colleagues
Piotr Indyk: colleagues
Anastasios Sidiropoulos: colleagues