The complexity of finding top-toda-equivalence-class members

Lane A. Hemaspaandra; Mitsunori Ogihara; Mohammed J. Zaki; Marius Zimand

doi:10.1007/978-3-540-24698-5_13

The complexity of finding top-toda-equivalence-class members

Lane A. Hemaspaandra, Mitsunori Ogihara, Mohammed J. Zaki, Marius Zimand

Research output: Chapter in Book/Report/Conference proceeding › Chapter

2 Scopus citations

Abstract

We identify two properties that for P-selective sets are effectively computable. Namely we show that, for any P-selective set, finding a string that is in a given length's top Toda equivalence class (very informally put, a string from ∑ⁿ that the set's P-selector function declares to be most likely to belong to the set) is FP∑₂^p computable, and we show that each P-selective set contains a weakly-P∑₂ ^p-rankable subset.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Martin Farach-Colton
Publisher	Springer Verlag
Pages	90-99
Number of pages	10
ISBN (Print)	3540212582, 9783540212584
DOIs	https://doi.org/10.1007/978-3-540-24698-5_13
State	Published - 2004
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2976
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-24698-5_13

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Cite this

Hemaspaandra, L. A., Ogihara, M., Zaki, M. J., & Zimand, M. (2004). The complexity of finding top-toda-equivalence-class members. In M. Farach-Colton (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 90-99). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2976). Springer Verlag. https://doi.org/10.1007/978-3-540-24698-5_13

The complexity of finding top-toda-equivalence-class members. / Hemaspaandra, Lane A.; Ogihara, Mitsunori; Zaki, Mohammed J.; Zimand, Marius.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Martin Farach-Colton. Springer Verlag, 2004. p. 90-99 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2976).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Hemaspaandra, LA, Ogihara, M, Zaki, MJ & Zimand, M 2004, The complexity of finding top-toda-equivalence-class members. in M Farach-Colton (ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2976, Springer Verlag, pp. 90-99. https://doi.org/10.1007/978-3-540-24698-5_13

Hemaspaandra LA, Ogihara M, Zaki MJ, Zimand M. The complexity of finding top-toda-equivalence-class members. In Farach-Colton M, editor, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 90-99. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-24698-5_13

Hemaspaandra, Lane A. ; Ogihara, Mitsunori ; Zaki, Mohammed J. ; Zimand, Marius. / The complexity of finding top-toda-equivalence-class members. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Martin Farach-Colton. Springer Verlag, 2004. pp. 90-99 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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