Communications of the ACM
A general lower bound on the number of examples needed for learning
Information and Computation
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
Negative Results for Equivalence Queries
Machine Learning
Teachability in computational learning
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Lower Bound Methods and Separation Results for On-Line Learning Models
Machine Learning - Computational learning theory
Decision trees for geometric models
SCG '93 Proceedings of the ninth annual symposium on Computational geometry
Journal of Computer and System Sciences
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?
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Generalized teaching dimensions and the query complexity of learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Machine Learning
Machine Learning
The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract)
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Uniform Characterizations of Polynomial-Query Learnabilities
DS '98 Proceedings of the First International Conference on Discovery Science
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
Abstract Combinatorial Characterizations of Exact Learning via Queries
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
On Sufficient Conditions to Identify in the Limit Classes of Grammars from Polynomial Time and Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Consistency Queries in Information Extraction
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Formal language identification: query learning vs. gold-style learning
Information Processing Letters
Learning via finitely many queries
Annals of Mathematics and Artificial Intelligence
Learning languages from positive data and a finite number of queries
Information and Computation
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning erasing pattern languages with queries
Theoretical Computer Science - Algorithmic learning theory (ALT 2000)
LARS: A learning algorithm for rewriting systems
Machine Learning
One-shot learners using negative counterexamples and nearest positive examples
Theoretical Computer Science
Insights to Angluin's Learning
Electronic Notes in Theoretical Computer Science (ENTCS)
Learning languages from positive data and a finite number of queries
Information and Computation
The subsumption lattice and query learning
Journal of Computer and System Sciences
A bibliographical study of grammatical inference
Pattern Recognition
Learning deterministically recognizable tree series: revisited
CAI'07 Proceedings of the 2nd international conference on Algebraic informatics
Theoretical Computer Science
Teaching learners with restricted mind changes
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Efficient algorithms for general active learning
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Analysis of perceptron-based active learning
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Teaching classes with high teaching dimension using few examples
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Learning languages from positive data and a finite number of queries
FSTTCS'04 Proceedings of the 24th international conference on Foundations of Software Technology and Theoretical Computer Science
Ten open problems in grammatical inference
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
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We begin with a brief tutorial on the problem of learning a finite concept class over a finite domain using membership queries and/or equivalence queries. We then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension, the sample exclusion dimension, the Vapnik-Chervonenkis dimension, the abstract identification dimension, and the general dimension.