Minimizing randomness in minimum spanning tree, parallel connectivity, and set maxima algorithms
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Architecture independent parallel selection with applications to parallel priority queues
Theoretical Computer Science
How (and why) to introduce Monte Carlo randomized algorithms into a basic algorithms course?
Journal of Computing Sciences in Colleges
On Floyd and Rivest's SELECT algorithm
Theoretical Computer Science
Randomized minimum spanning tree algorithms using exponentially fewer random bits
ACM Transactions on Algorithms (TALG)
Feasible Iteration of Feasible Learning Functionals
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
Comparison-based time-space lower bounds for selection
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
A simpler implementation and analysis of Chazelle's soft heaps
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Comparison-based time-space lower bounds for selection
ACM Transactions on Algorithms (TALG)
Enriching introductory programming courses with non-intuitive probability experiments component
Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education
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Improving a long standing result of Bent and John [Proceedings of the 17th Annual ACM Symposium on Theory of Computing, Providence, RI, 1985, pp. 213--216], and extending a recent result of Dor, Håstad, Ulfberg, and Zwick [ SIAM J. Discrete Math., 14 (2001), pp. 299--311], we obtain a $(2{+}\epsilon)n$ lower bound (for some fixed $\epsilon0$) on the number of comparisons required, in the worst case, for selecting the median of n elements.