D. Eppstein. Persistence, offline algorithms, and space compaction. Technical Report 91-54, Dept. Information and Comput. Sci., U. C. Irvine, 1991. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Iterated Nearest Neighbors and Finding Minimal Polytopes - Eppstein, Erickson (1994) (34 citations) Self-citation (Eppstein) (Correct)
....slab, we add it to the list. The positions to add new points into the list can be found in time O(n)ifthepoints are already sorted by x coordinate. Wewould like our data structure to reconstruct the state of this list at each time in the sweep. This is a persistent offline data structure problem [18], in whichweperformanumber of updates (insertions into a linked list) and must then query differentversions of the data structure (the list at different times in the sweep) Wemaintain, at eachpoint in the left to rightsweep, a partition of the sorted list of points into chunks of between m= log ....
D. Eppstein. Persistence, offline algorithms, and space compaction. Technical Report 91-54, Dept. Information and Comput. Sci., U. C. Irvine, 1991.
Iterated Nearest Neighbors and Finding Minimal Polytopes - Eppstein, Erickson (1994) (34 citations) Self-citation (Eppstein) (Correct)
....we add it to the list. The positions to add new points into the list can be found in time O(n) if the points are already sorted by x coordinate. We would like our data structure to reconstruct the state of this list at each time in the sweep. This is a persistent offline data structure problem [18], in which we perform a number of updates (insertions into a linked list) and must then query different versions of the data structure (the list at different times in the sweep) We maintain, at each point in the left to right sweep, a partition of the sorted list of points into chunks of between ....
D. Eppstein. Persistence, offline algorithms, and space compaction. Technical Report 91-54, Dept. Information and Comput. Sci., U. C. Irvine, 1991.
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