No. 318 on SWAT 88: 1st Scandinavian workshop on algorithm theory
Journal of the ACM (JACM)
Random number generators: good ones are hard to find
Communications of the ACM
Introduction to algorithms
The information theory bound is tight for selection in a heap
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Fundamentals of algorithmics
Analysis of algorithms: computational methods and mathematical tools
Analysis of algorithms: computational methods and mathematical tools
Analysis of Hoare's FIND algorithm with median-of-three partition
Random Structures & Algorithms - Special issue: average-case analysis of algorithms
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
SIAM Journal on Computing
Expected time bounds for selection
Communications of the ACM
Communications of the ACM
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Generalized selection and ranking (Preliminary Version)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Fundamentals of Applied Probability Theory
Fundamentals of Applied Probability Theory
Two entropies of a generalized sorting problem
Journal of Computer and System Sciences
Journal of Computer and System Sciences
Journal of Computer and System Sciences
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Approximate range mode and range median queries
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Optimal selection and sorting via dynamic programming
Journal of Experimental Algorithmics (JEA)
Extending high-dimensional indexing techniques pyramid and iminmax(θ): lessons learned
BNCOD'13 Proceedings of the 29th British National conference on Big Data
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We present an efficient algorithm for the approximate median selection problem. The algorithm works in-place; it is fast and easy to implement. For a large array it returns, with high probability, a very close estimate of the true median. The running time is linear in the length n of the input. The algorithm performs fewer than 4/3n comparisons and 1/3n exchanges on the average. We present analytical results of the performance of the algorithm, as well as experimental illustrations of its precision.