Publication | Open Access
Privately releasing conjunctions and the statistical query barrier
102
Citations
26
References
2011
Year
Unknown Venue
Computational Complexity TheoryEngineeringComputational ComplexityStatistical Queries CStatistical Query BarrierSyntaxStatistical QueriesInformation RetrievalData ScienceComputational LinguisticsLanguage StudiesStatisticsData PrivacyPrivate Information RetrievalComputer ScienceAlgorithmic Information TheoryDifferential PrivacyPrivacyPrivacy LeakageQuery OptimizationRelational QueriesStatistical InferenceStatistical DatabaseApproximate Query AnsweringLinguisticsAgnostic Learning Complexity
Suppose we would like to know all answers to a set of statistical queries C on a data set up to small error, but we can only access the data itself using statistical queries. A trivial solution is to exhaustively ask all queries in C. Can we do any better? We show that the number of statistical queries necessary and sufficient for this task is---up to polynomial factors---equal to the agnostic learning complexity of C in Kearns' statistical query (SQ)model. This gives a complete answer to the question when running time is not a concern.
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