Systems that learn: an introduction to learning theory for cognitive and computer scientists
Systems that learn: an introduction to learning theory for cognitive and computer scientists
Theory of recursive functions and effective computability
Theory of recursive functions and effective computability
Probability and plurality for aggregations of learning machines
Information and Computation
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Inductive inference with bounded number of mind changes
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Relations between probabilistic and team one-shot learners (extended abstract)
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
Breaking the probability ½ barrier in FIN-type learning
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Probability is more powerful than team for language identification from positive data
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
On the role of procrastination in machine learning
Information and Computation
Choosing a learning team: a topological approach
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Inductive Inference: Theory and Methods
ACM Computing Surveys (CSUR)
An Introduction to the General Theory of Algorithms
An Introduction to the General Theory of Algorithms
Topological Considerations in Composing Teams of Learning Machines
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report
On Identification by Teams and Probabilistic Machines
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report
Towards Reduction Argumentf for FINite Learning
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report
The power of procrastination in inductive inference: How it depends on used ordinal notations
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
The Power of Probabilism in Popperian FINite Learning (extended abstract)
AII '92 Proceedings of the International Workshop on Analogical and Inductive Inference
Use of Reduction Arguments in Determining Popperian FIN-Type Learning Capabilities
ALT '93 Proceedings of the 4th International Workshop on Algorithmic Learning Theory
Three Decades of Team Learning
AII '94 Proceedings of the 4th International Workshop on Analogical and Inductive Inference: Algorithmic Learning Theory
Probabilistic inductive inference: a survey
Theoretical Computer Science
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