Abstract | ||
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We use here the results on the influence graph(1) to adapt them for particular cases where additional information is available. In some cases, it is possible to improve the expected randomized complexity of algorithms from O(n log n) to O(n log⋆ n). This technique applies in the following applications : triangulation of a simple polygon, skeleton of a simple polygon, Delaunay triangulation of points knowing the EMST (euclidean minimum spanning tree). Keywords: Randomized algorithms, Influence graph, Conflict graph, Skeleton of a polygon, Delaunay triangulation, Euclidean minimum span- ning tree |
Year | Venue | Keywords |
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1992 | Int. J. Comput. Geometry Appl. | conflict graph,delaunay triangulation,skeleton of a polygon,euclidean minimum span- ning tree,randomized algorithms,influence graph |
DocType | Volume | Issue |
Journal | 2 | 1 |
Citations | PageRank | References |
12 | 0.99 | 11 |
Authors | ||
1 |
Name | Order | Citations | PageRank |
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Olivier Devillers | 1 | 184 | 23.75 |