Computational geometry: an introduction
Computational geometry: an introduction
Fast linear expected-time alogorithms for computing maxima and convex hulls
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
On the Average Number of Maxima in a Set of Vectors and Applications
Journal of the ACM (JACM)
Proceedings of the 17th International Conference on Data Engineering
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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The maxima-finding is a fundamental problem in computational geometry with many applications. In this paper, a volume first maxima-finding algorithm is proposed. It is proved that the expected running time of the algorithm is N+o(N) when choosing points from CI distribution, which is a new theoretical result when the points belong to d(2) dimensional space. Experimental results and theoretical analysis indicate that the algorithm runs faster than the Move-To-Front maxima-finding algorithm.