Lower bounds on learning random structures with statistical queries

Dana Angluin; David Eisenstat; Leonid Kontorovich; Lev Reyzin

doi:10.1007/978-3-642-16108-7_18

Lower bounds on learning random structures with statistical queries

Dana Angluin, David Eisenstat, Leonid Kontorovich, Lev Reyzin

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries with respect to an arbitrary distribution on examples.

Original language	English
Title of host publication	Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings
Pages	194-208
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-642-16108-7_18
State	Published - 19 Nov 2010
Event	21st International Conference on Algorithmic Learning Theory, ALT 2010 - Canberra, ACT, Australia Duration: 6 Oct 2010 → 8 Oct 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6331 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International Conference on Algorithmic Learning Theory, ALT 2010
Country/Territory	Australia
City	Canberra, ACT
Period	6/10/10 → 8/10/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-642-16108-7_18

Cite this

Angluin, D., Eisenstat, D., Kontorovich, L., & Reyzin, L. (2010). Lower bounds on learning random structures with statistical queries. In Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings (pp. 194-208). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6331 LNAI). https://doi.org/10.1007/978-3-642-16108-7_18

Angluin, Dana ; Eisenstat, David ; Kontorovich, Leonid et al. / Lower bounds on learning random structures with statistical queries. Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings. 2010. pp. 194-208 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries with respect to an arbitrary distribution on examples.",

author = "Dana Angluin and David Eisenstat and Leonid Kontorovich and Lev Reyzin",

year = "2010",

month = nov,

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doi = "10.1007/978-3-642-16108-7_18",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Angluin, D, Eisenstat, D, Kontorovich, L & Reyzin, L 2010, Lower bounds on learning random structures with statistical queries. in Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6331 LNAI, pp. 194-208, 21st International Conference on Algorithmic Learning Theory, ALT 2010, Canberra, ACT, Australia, 6/10/10. https://doi.org/10.1007/978-3-642-16108-7_18

Lower bounds on learning random structures with statistical queries. / Angluin, Dana; Eisenstat, David; Kontorovich, Leonid et al.
Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings. 2010. p. 194-208 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6331 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Eisenstat, David

AU - Kontorovich, Leonid

AU - Reyzin, Lev

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N2 - We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries with respect to an arbitrary distribution on examples.

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Angluin D, Eisenstat D, Kontorovich L, Reyzin L. Lower bounds on learning random structures with statistical queries. In Algorithmic Learning Theory - 21st International Conference, ALT 2010, Proceedings. 2010. p. 194-208. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-16108-7_18

Lower bounds on learning random structures with statistical queries

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