On the learnability of recursively enumerable languages from good examples
Theoretical Computer Science
On the power of incremental learning
Theoretical Computer Science
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
On the Strength of Incremental Learning
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Learning Recursive Concepts with Anomalies
ALT '00 Proceedings of the 11th International Conference on Algorithmic Learning Theory
Variants of iterative learning
Theoretical Computer Science
Learning via finitely many queries
Annals of Mathematics and Artificial Intelligence
On learning to coordinate: random bits help, insightful normal forms, and competency isomorphisms
Journal of Computer and System Sciences - Special issue: Learning theory 2003
From learning in the limit to stochastic finite learning
Theoretical Computer Science - Algorithmic learning theory
Learning a subclass of regular patterns in polynomial time
Theoretical Computer Science - Algorithmic learning theory
On the data consumption benefits of accepting increased uncertainty
Theoretical Computer Science
Results on memory-limited U-shaped learning
Information and Computation
Some natural conditions on incremental learning
Information and Computation
Non-U-shaped vacillatory and team learning
Journal of Computer and System Sciences
Learning indexed families of recursive languages from positive data: A survey
Theoretical Computer Science
Learning recursive functions: A survey
Theoretical Computer Science
U-shaped, iterative, and iterative-with-counter learning
Machine Learning
Resource Restricted Computability Theoretic Learning: Illustrative Topics and Problems
CiE '07 Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World
Parallelism Increases Iterative Learning Power
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Learning with Temporary Memory
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Parallelism increases iterative learning power
Theoretical Computer Science
U-shaped, iterative, and iterative-with-counter learning
COLT'07 Proceedings of the 20th annual conference on Learning theory
Iterative learning of simple external contextual languages
Theoretical Computer Science
Incremental learning with temporary memory
Theoretical Computer Science
Iterative learning from texts and counterexamples using additional information
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Incremental learning with ordinal bounded example memory
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Solutions to open questions for non-u-shaped learning with memory limitations
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Teaching randomized learners with feedback
Information and Computation
Automatic learners with feedback queries
CiE'11 Proceedings of the 7th conference on Models of computation in context: computability in Europe
Iterative learning from positive data and counters
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Towards a better understanding of incremental learning
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Memory-limited u-shaped learning
COLT'06 Proceedings of the 19th annual conference on Learning Theory
String extension learning using lattices
LATA'10 Proceedings of the 4th international conference on Language and Automata Theory and Applications
Learning with ordinal-bounded memory from positive data
Journal of Computer and System Sciences
Learning in the limit with lattice-structured hypothesis spaces
Theoretical Computer Science
Memory-limited non-U-shaped learning with solved open problems
Theoretical Computer Science
Iterative learning from positive data and counters
Theoretical Computer Science
Automatic learners with feedback queries
Journal of Computer and System Sciences
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