Learning classes of approximations to non-recursive functions.
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Publication:1853518
DOI10.1016/S0304-3975(01)00405-4zbMath1061.68085OpenAlexW2012806533MaRDI QIDQ1853518
Thomas Zeugmann, Frank Stephan
Publication date: 21 January 2003
Published in: Theoretical Computer Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0304-3975(01)00405-4
Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05) Recursively (computably) enumerable sets and degrees (03D25)
Related Items (3)
Learning recursive functions: A survey ⋮ Consistent and coherent learning with \(\delta \)-delay ⋮ On the interplay between inductive inference of recursive functions, complexity theory and recursive numberings
Cites Work
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- Comparison of identification criteria for machine inductive inference
- One-sided error probabilistic inductive inference and reliable frequency identification
- Research in the theory of inductive inference by GDR mathematicians - A survey
- Some natural properties of strong-identification in inductive inference
- Classical recursion theory. Vol. II
- Robust learning aided by context
- Avoiding coding tricks by hyperrobust learning
- Robust behaviorally correct learning.
- Robust separations in inductive inference
- ON THE NONBOUNDABILITY OF TOTAL EFFECTIVE OPERATORS
- Transformations that preserve learnability
- Inductive inference of formal languages from positive data
- Über die Erfüllung gewisser Erhaltungssätze durch Kompliziertheitsmasse
- Toward a mathematical theory of inductive inference
- Inductive inference of recursive functions: Qualitative theory
- A Machine-Independent Theory of the Complexity of Recursive Functions
- On Effectively Computable Operators
- Language identification in the limit
- Robust learning is rich
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