Learning read-once formulas using membership queries
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Learning read-once formulas with queries
Journal of the ACM (JACM)
Cryptographic limitations on learning Boolean formulae and finite automata
Journal of the ACM (JACM)
A framework for polynomial-time query learnability
Mathematical Systems Theory
Structural analysis of polynomial-time query learnability
Mathematical Systems Theory
When won't membership queries help?
Selected papers of the 23rd annual ACM symposium on Theory of computing
Oracles and queries that are sufficient for exact learning
Journal of Computer and System Sciences
How many queries are needed to learn?
Journal of the ACM (JACM)
Complexity theoretic hardness results for query learning
Computational Complexity
Machine Learning
Machine Learning
A general dimension for query learning
Journal of Computer and System Sciences
Characterizing statistical query learning: simplified notions and proofs
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
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The general dimension is a combinatorial measure that characterizes the number of queries needed to learn a concept class. We use this notion to show that any p-evaluatable concept class with polynomial query complexity can be learned in polynomial time with the help of an oracle in the polynomial hierarchy, where the complexity of the required oracle depends on the query-types used by the learning algorithm. In particular, we show that for subset and superset queries an oracle in Σ3P suffices. Since the concept class of DNF formulas has polynomial query complexity with respect to subset and superset queries with DNF formulas as hypotheses, it follows that DNF formulas are properly learnable in polynomial time with subset and superset queries and the help of an oracle in Σ3P. We also show that the required oracle in our main theorem cannot be replaced by an oracle in a lower level of the polynomial-time hierarchy, unless the hierarchy collapses.