Improved bounds for the randomized decision tree complexity of recursive majority

4Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We consider the randomized decision tree complexity of the recursive 3-majority function. For evaluating height h formulae, we prove a lower bound for the δ-two-sided-error randomized decision tree complexity of (1 - 2δ)(5/2) h , improving the lower bound of (1 - 2δ)(7/3) h given by Jayram, Kumar, and Sivakumar (STOC '03). Second, we improve the upper bound by giving a new zero-error randomized decision tree algorithm that has complexity at most (1.007) •2.64946 h . The previous best known algorithm achieved complexity (1.004) •2.65622 h . The new lower bound follows from a better analysis of the base case of the recursion of Jayram et al. The new algorithm uses a novel "interleaving" of two recursive algorithms. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Magniez, F., Nayak, A., Santha, M., & Xiao, D. (2011). Improved bounds for the randomized decision tree complexity of recursive majority. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6755 LNCS, pp. 317–329). https://doi.org/10.1007/978-3-642-22006-7_27

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free