Computational learning theory: survey and selected bibliography
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
General bounds on the number of examples needed for learning probabilistic concepts
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
Learning from a consistently ignorant teacher
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning linear threshold functions in the presence of classification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning with unreliable boundary queries
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Specification and simulation of statistical query algorithms for efficiency and noise tolerance
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Noise-tolerant learning near the information-theoretic bound
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Computational sample complexity
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Learning from examples with unspecified attribute values (extended abstract)
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Improved lower bounds for learning from noisy examples: an information-theoretic approach
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Efficient noise-tolerant learning from statistical queries
Journal of the ACM (JACM)
Sample-efficient strategies for learning in the presence of noise
Journal of the ACM (JACM)
A Quasi-Metric for Machine Learning
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
A Probabilistic Identification Result
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
A Theory of Hypothesis Finding in Clausal Logic
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Hypothesis finding based on upward refinement of residue hypotheses
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
Information Sciences—Informatics and Computer Science: An International Journal
On using extended statistical queries to avoid membership queries
The Journal of Machine Learning Research
A Generalization Model Based on OI-implication for Ideal Theory Refinement
Fundamenta Informaticae - Intelligent Systems
Classification algorithm sensitivity to training data with non representative attribute noise
Decision Support Systems
Kernel Functions Based on Derivation
New Frontiers in Applied Data Mining
Algorithms for learning regular expressions from positive data
Information and Computation
ILP with noise and fixed example size: a Bayesian approach
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Towards a logical reconstruction of CF-induction
JSAI'07 Proceedings of the 2007 conference on New frontiers in artificial intelligence
Extending EBG to term-rewriting systems
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Learning from positive data based on the MINL strategy with refinement operators
JSAI-isAI'09 Proceedings of the 2009 international conference on New frontiers in artificial intelligence
Algorithms for learning regular expressions
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Inductive logic programming: yet another application of logic
INAP'05 Proceedings of the 16th international conference on Applications of Declarative Programming and Knowledge Management
DNF hypotheses in explanatory induction
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
A Generalization Model Based on OI-implication for Ideal heory Refinement
Fundamenta Informaticae - Intelligent Systems
PAC-Learning with general class noise models
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
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