Preprocessing power weighted shortest path data using a s-Well Separated Pair Decomposition
For \(s\) \(>\) 0, we consider an algorithm that computes all \(s\)-well separated pairs in certain point sets in \(\mathbb{R}^{n}\), \(n\) \(>1\). For an integer \(K\) \(>1\), we also consider an algorithm that is a permutation of Dijkstra's algorithm, that computes \(K\)-nearest neig...
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Published in | arXiv.org |
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Main Authors | , |
Format | Paper |
Language | English |
Published |
Ithaca
Cornell University Library, arXiv.org
16.05.2021
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Subjects | |
Online Access | Get full text |
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Summary: | For \(s\) \(>\) 0, we consider an algorithm that computes all \(s\)-well separated pairs in certain point sets in \(\mathbb{R}^{n}\), \(n\) \(>1\). For an integer \(K\) \(>1\), we also consider an algorithm that is a permutation of Dijkstra's algorithm, that computes \(K\)-nearest neighbors using a certain power weighted shortest path metric in \(\mathbb{R}^{n}\), \(n\) \(>\) \(1\). We describe each algorithm and their respective dependencies on the input data. We introduce a way to combine both algorithms into a fused algorithm. Several open problems are given for future research. |
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ISSN: | 2331-8422 |