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Approximation algorithms for low-distortion embeddings into low-dimensional spaces
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Source Symposium on Discrete Algorithms archive
Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms table of contents
Vancouver, British Columbia
SESSION: Session 1C table of contents
Pages: 119 - 128  
Year of Publication: 2005
ISBN:0-89871-585-7
Authors
Mihai Bǎdoiu  MIT Computer Science and Artificial Intelligence Laboratory; Cambridge, MA
Kedar Dhamdhere  Carnegie Mellon University; Pittsburgh, PA
Anupam Gupta  Carnegie Mellon University; Pittsburgh, PA
Yuri Rabinovich  University of Haifa; Haifa, Iarael
Harald Räcke  Carnegie Mellon University; Pittsburgh, PA
R. Ravi  Carnegie Mellon University; Pittsburgh, PA
Anastasios Sidiropoulos  MIT Computer Science and Artificial Intelligence Laboratory; Cambridge, MA
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
: SIAM Activity Group on Discrete Mathematics
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 34,   Citation Count: 10
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ABSTRACT

We present several approximation algorithms for the problem of embedding metric spaces into a line, and into the two-dimensional plane. Among other results, we give an O(√n)-approximation algorithm for the problem of finding a line embedding of a metric induced by a given unweighted graph, that minimizes the (standard) multiplicative distortion. We give an improved Õ(n1/3) approximation for the case of metrics generated by unweighted trees. This is the first result of this type.


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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CITED BY  10
Collaborative Colleagues:
Mihai Bǎdoiu: colleagues
Kedar Dhamdhere: colleagues
Anupam Gupta: colleagues
Yuri Rabinovich: colleagues
Harald Räcke: colleagues
R. Ravi: colleagues
Anastasios Sidiropoulos: colleagues