Communications of the ACM
The knowledge complexity of interactive proof-systems
STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Learning regular sets from queries and counterexamples
Information and Computation
Negative Results for Equivalence Queries
Machine Learning
Identifying μ-formula decision trees with queries
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Inductive inference: an abstract approach
COLT '88 Proceedings of the first annual workshop on Computational learning theory
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Learning read-once formulas over fields and extended bases
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Machine Learning
Machine Learning
Learning Read-Once Formulas with Queries
Learning Read-Once Formulas with Queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Being taught can be faster than asking questions
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
DNF—if you can't learn'em, teach'em: an interactive model of teaching
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Teachers, learners and black boxes
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
An apprentice learning model (extended abstract)
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Decision lists and related Boolean functions
Theoretical Computer Science
Learning DFA from Simple Examples
Machine Learning
Measuring teachability using variants of the teaching dimension
Theoretical Computer Science
Computer Vision and Image Understanding
Learning-testing process in classroom: An empirical simulation model
Computers & Education
Recent Developments in Algorithmic Teaching
LATA '09 Proceedings of the 3rd International Conference on Language and Automata Theory and Applications
Recursive teaching dimension, learning complexity, and maximum classes
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Teaching randomized learners with feedback
Information and Computation
Models of Cooperative Teaching and Learning
The Journal of Machine Learning Research
Teaching memoryless randomized learners without feedback
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Teaching learners with restricted mind changes
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
COLT'06 Proceedings of the 19th 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
Massive online teaching to bounded learners
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
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Goldman and Kearns [GK91] recently introduced a notion of the teaching dimension of a concept class. The teaching dimension is intended to capture the combinatorial difficulty of teaching a concept class. We present a computational analog which allows us to make statements about bounded-complexity teachers and learners, and we extend the model by incorporating trusted information. Under this extended model, we modify algorithms for learning several expressive classes in the exact identification model of Angluin [Ang88]. We study the relationships between variants of these models, and also touch on a relationship with distribution-free learning.