Random inequality constraint systems with few variables
Mathematical Programming: Series A and B
On the average number of maxima in a set of vectors
Information Processing Letters
Combinatorial variations on multidimensional quadtrees
Journal of Combinatorial Theory Series A
Mellin transforms and asymptotics: finite differences and Rice's integrals
Theoretical Computer Science - Special volume on mathematical analysis of algorithms (dedicated to D. E. Knuth)
Hypergeometrics and the cost structure of quadtrees
Random Structures & Algorithms
On the Average Number of Maxima in a Set of Vectors and Applications
Journal of the ACM (JACM)
Lecture Notes on Bucket Algorithms
Lecture Notes on Bucket Algorithms
Notes on the variance of the number of maxima in three dimensions
Random Structures & Algorithms
Techniques for highly multiobjective optimisation: some nondominated points are better than others
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Noncommutative algebra, multiple harmonic sums and applications in discrete probability
Journal of Symbolic Computation
Quantifying the effects of objective space dimension in evolutionary multiobjective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Maxima-finding algorithms for multidimensional samples: A two-phase approach
Computational Geometry: Theory and Applications
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We derive a Berry-Esseen bound, essentially of the order of the square of the standard deviation, for the number of maxima in random samples from (0, 1)d. The bound is, although not optimal, the first of its kind for the number of maxima in dimensions higher than two. The proof uses Poisson processes and Stein's method. We also propose a new method for computing the variance and derive an asymptotic expansion. The methods of proof we propose are of some generality and applicable to other regions such as d-dimensional simplex.