Finding the αn-th largest element

We describe an algorithm for selecting the αn-th largest element (where 0<α<1), from a totally ordered set ofn elements, using at most (1+(1+o(1))H(α))·n comparisons whereH(α) is the binary entropy function and theo(1) stands for a function that tends to 0 as α tends to 0. For small values of α this is almost the best possible as there is a lower bound of about (1+H(α))·n comparisons. The algorithm obtained beats the global 3n upper bound of Schönhage, Paterson and Pippenger for α<1/3.

[1]  Samuel W. Bent,et al.  Finding the median requires 2n comparisons , 1985, STOC '85.

[2]  Uri Zwick,et al.  Selecting the median , 1995, SODA '95.

[3]  John W. John A New Lower Bound for the Set-Partitioning Problem , 1988, SIAM J. Comput..

[4]  Prakash V. Ramanan,et al.  New Algorithms for Selection , 1984, J. Algorithms.

[5]  Ronald L. Rivest,et al.  Expected time bounds for selection , 1975, Commun. ACM.

[6]  Tatsuya Motoki A Note on Upper Bounds for the Selection Problem , 1982, Inf. Process. Lett..

[7]  F. Yao ON LOWER BOUNDS FOR SELECTION PROBLEMS , 1974 .

[8]  Chee-Keng Yap,et al.  New upper bounds for selection , 1976, CACM.

[9]  Manuel Blum,et al.  Time Bounds for Selection , 1973, J. Comput. Syst. Sci..

[10]  Arnold Schönhage,et al.  Finding the Median , 1976, J. Comput. Syst. Sci..

[11]  J. Ian Munro,et al.  Average case selection , 1989, JACM.