Read-thrice DNF is hard to learn with membership and equivalence queries

Howard Aizenstein, Lisa Hellerstein, Leonard Pitt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A general technique is developed to obtain nonlearnability results in the model of exact learning from equivalence and membership queries. The technique is applied to show that, assuming NP not=co-NP, there does not exist a polynomial-time membership and equivalence query algorithm for exactly learning read-thrice DNF formulas-boolean formulas in disjunctive normal form where each variable appears at most three times. This result adds evidence to the conjecture that DNF is hard to learn in the membership and equivalence query model.

Original languageEnglish (US)
Title of host publicationProceedings - 33rd Annual Symposium on Foundations of Computer Science, FOCS 1992
PublisherIEEE Computer Society
Pages523-532
Number of pages10
ISBN (Electronic)0818629002
DOIs
StatePublished - 1992
Event33rd Annual Symposium on Foundations of Computer Science, FOCS 1992 - Pittsburgh, United States
Duration: Oct 24 1992Oct 27 1992

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
Volume1992-October
ISSN (Print)0272-5428

Conference

Conference33rd Annual Symposium on Foundations of Computer Science, FOCS 1992
CountryUnited States
CityPittsburgh
Period10/24/9210/27/92

ASJC Scopus subject areas

  • Computer Science(all)

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