| Sublinear-time approximation of Euclidean minimum spanning tree |
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Symposium on Discrete Algorithms
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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
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Authors
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Artur Czumaj
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New Jersey Institute of Technology, Newark, NJ
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Funda Ergün
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Case Western Reserve University, Cleveland, OH
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Lance Fortnow
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NEC Research, Princeton, NJ
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Avner Magen
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University of Toronto, Toronto, Ontario, Canada
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Ilan Newman
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University of Haifa, Haifa, Israel
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Ronitt Rubinfeld
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NEC Research, Princeton, NJ
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Christian Sohler
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University of Paderborn, Paderbom, Germany
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Society for Industrial and Applied Mathematics
Philadelphia, PA, USA
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| Bibliometrics |
Downloads (6 Weeks): 4, Downloads (12 Months): 56, Citation Count: 5
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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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[doi> 10.1145/225058.225191]
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