Name
Abstract | ||
|---|---|---|
Simple, two-phase algorithms are devised for finding the maxima of multidimensional point samples, one of the very first problems studied in computational geometry. The algorithms are easily coded and modified for practical needs. The expected complexity of some measures related to the performance of the algorithms is analyzed. We also compare the efficiency of the algorithms with a few major ones used in practice, and apply our algorithms to find the maximal layers and the longest common subsequences of multiple sequences. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.comgeo.2011.08.001 | Comput. Geom. |
Keywords | Field | DocType |
computational geometry,multiple sequence,longest common subsequence,two-phase approach,two-phase algorithm,maximal layer,expected complexity,multidimensional point sample,multidimensional sample,maxima-finding algorithm,practical need,multi objective optimization,dominance | Skyline,Combinatorics,Computational geometry,Algorithm,Probabilistic analysis of algorithms,Multi-objective optimization,Two phase approach,Maxima,Mathematics,Randomized algorithms as zero-sum games | Journal |
Volume | Issue | ISSN |
45 | 1-2 | 0925-7721 |
Citations | PageRank | References |
2 | 0.38 | 39 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei‐Mei Chen | 1 | 57 | 9.26 |
| Hsien-Kuei Hwang | 2 | 365 | 38.02 |
| Tsung-Hsi Tsai | 3 | 81 | 8.20 |