Communications of the ACM
Learning regular sets from queries and counterexamples
Information and Computation
Negative Results for Equivalence Queries
Machine Learning
On-line learning with an oblivious environment and the power of randomization
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
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)
Machine Learning
Machine Learning
Simple PAC Learning of Simple Decision Lists
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
How Many Queries Are Needed to Learn One Bit of Information?
Annals of Mathematics and Artificial Intelligence
Theoretical Computer Science - Special issue: Algorithmic learning theory
A general dimension for query learning
Journal of Computer and System Sciences
Query Learning and Certificates in Lattices
ALT '08 Proceedings of the 19th international conference on Algorithmic 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.