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Sublinear-time approximation of Euclidean minimum spanning tree
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Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms table of contents
Baltimore, Maryland
SESSION: Session 12A table of contents
Pages: 813 - 822  
Year of Publication: 2003
ISBN:0-89871-538-5
Authors
Artur Czumaj  New Jersey Institute of Technology, Newark, NJ
Funda Ergün  Case Western Reserve University, Cleveland, OH
Lance Fortnow  NEC Research, Princeton, NJ
Avner Magen  University of Toronto, Toronto, Ontario, Canada
Ilan Newman  University of Haifa, Haifa, Israel
Ronitt Rubinfeld  NEC Research, Princeton, NJ
Christian Sohler  University of Paderborn, Paderbom, Germany
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 finding the weight of a Euclidean minimum spanning tree for a set of n points in ℝd. We focus on the situation when the input point set is supported by certain basic (and commonly used) geometric data structures that can provide efficient access to the input in a structured way. We present an algorithm that estimates with high probability the weight of a Euclidean minimum spanning tree of a set of points to within 1 + ε using only Õ(√ poly(1/ε)) queries for constant d. The algorithm assumes that the input is supported by a minimal bounding cube enclosing it, by orthogonal range queries, and by cone approximate nearest neighbors queries.


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:
Artur Czumaj: colleagues
Funda Ergün: colleagues
Lance Fortnow: colleagues
Avner Magen: colleagues
Ilan Newman: colleagues
Ronitt Rubinfeld: colleagues
Christian Sohler: colleagues

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