Communications of the ACM
Learning regular sets from queries and counterexamples
Information and Computation
Negative Results for Equivalence Queries
Machine Learning
Learning simple concepts under simple distributions
SIAM Journal on Computing
On the power of equivalence queries
Euro-COLT '93 Proceedings of the first European conference on Computational learning theory
How many queries are needed to learn?
Journal of the ACM (JACM)
Inference of Reversible Languages
Journal of the ACM (JACM)
Machine Learning
Machine Learning
Learning decision lists and trees with equivalence-queries
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Simple PAC Learning of Simple Decision Lists
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Uniform Characterizations of Polynomial-Query Learnabilities
DS '98 Proceedings of the First International Conference on Discovery Science
Learnability and Definability in Trees and Similar Structures
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
A General Dimension for Approximately Learning Boolean Functions
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
The Consistency Dimension, Compactness, and Query Learning
CSL '99 Proceedings of the 13th International Workshop and 8th Annual Conference of the EACSL on Computer Science Logic
How Many Queries Are Needed to Learn One Bit of Information?
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
A General Dimension for Exact Learning
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
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We prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses obtained by restricting the instance space. Then we propose and study two models of query learning in which there is a probability distribution on the instance space, both as an application of the tools developed from the combinatorial characterization and as models of independent interest.