On-line learning of rectangles
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Asking questions to minimize errors
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Learning unions of two rectangles in the plane with equivalence queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On-line learning of rectangles in noisy environments
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Lower bounds for PAC learning with queries
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On the complexity of function learning
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Learning unions of boxes with membership and equivalence queries
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Geometrical concept learning and convex polytopes
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning with queries but incomplete information (extended abstract)
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Simulating access to hidden information while learning
STOC '94 Proceedings of the twenty-sixth 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
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant parallel learning of geometric concepts
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Exact Learning of Formulas in Parallel
Machine Learning
Malicious Omissions and Errors in Answers to Membership Queries
Machine Learning
Structural results about exact learning with unspecified attribute values
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
The query complexity of finding local minima in the lattice
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
On theory revision with queries
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Learning Function-Free Horn Expressions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
On the Sample Complexity for Nonoverlapping Neural Networks
Machine Learning
The query complexity of finding local minima in the lattice
Information and Computation
Product Unit Neural Networks with Constant Depth and Superlinear VC Dimension
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Learnability and Definability in Trees and Similar Structures
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
How Many Missing Answers Can Be Tolerated by Query Learners?
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
Lower Bounds for the Complexity of Learning Half-Spaces with Membership Queries
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
On the Sample Complexity for Neural Trees
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Learning elementary formal systems with queries
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
Limitations of learning via embeddings in euclidean half spaces
The Journal of Machine Learning Research
Theoretical Computer Science - Special issue: Algorithmic learning theory
Theory revision with queries: horn, read-once, and parity formulas
Artificial Intelligence
Complexity parameters for first order classes
Machine Learning
Theoretical Computer Science
Learning conditional preference networks
Artificial Intelligence
Algorithms and theory of computation handbook
Recursive teaching dimension, learning complexity, and maximum classes
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
On optimal learning algorithms for multiplicity automata
COLT'06 Proceedings of the 19th annual conference on Learning Theory
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We consider the complexity of concept learning in various common models for on-line learning, focusing on methods for proving lower bounds to the learning complexity of a concept class. Among others, we consider the model for learning with equivalence and membership queries. For this model we give lower bounds on the number of queries that are needed to learn a concept class {\cal C} in terms of the Vapnik-Chervonenkis dimension of {\cal C}, and in terms of the complexity of learning {\cal C} with arbitrary equivalence queries. Furthermore, we survey other known lower bound methods and we exhibit all known relationships between learning complexities in the models considered and some relevant combinatorial parameters. As it turns out, the picture is almost complete. This paper has been written so that it can be read without previous knowledge of Computational Learning Theory.