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Ordinal embeddings of minimum relaxation: general properties, trees, and ultrametrics
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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 7C table of contents
Pages: 650 - 659  
Year of Publication: 2005
ISBN:0-89871-585-7
Authors
Noga Alon  Tel Aviv University, Tel Aviv, Israel
Mihai Bădoiu  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Erik D. Demaine  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Martin Farach-Colton  Rutgers University
MohammadTaghi Hajiaghayi  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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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ABSTRACT

We introduce a new notion of embedding, called minimum-relaxation ordinal embedding, parallel to the standard notion of minimum-distortion (metric) embedding. In an ordinal embedding, it is the relative order between pairs of distances, and not the distances themselves, that must be preserved as much as possible. The (multiplicative) relaxation of an ordinal embedding is the maximum ratio between two distances whose relative order is inverted by the embedding. We develop several worst-case bounds and approximation algorithms on ordinal embedding. In particular, we establish that ordinal embedding has many qualitative differences from metric embedding, and capture the ordinal behavior of ultrametrics and shortest-path metrics of unweighted trees.


REFERENCES

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Collaborative Colleagues:
Noga Alon: colleagues
Mihai Bădoiu: colleagues
Erik D. Demaine: colleagues
Martin Farach-Colton: colleagues
MohammadTaghi Hajiaghayi: colleagues
Anastasios Sidiropoulos: colleagues