Computational Learning Theory
In computational learning theory, learnability is the mathematical analysis of machine learning. It is also employed in language acquisition in arguments within linguistics.
Frameworks include:
- Language identification in the limit proposed in 1967 by E. Mark Gold. Subsequently known as Algorithmic learning theory.
- Probably approximately correct learning (PAC learning) proposed in 1984 by Leslie Valiant
Read more about this topic: Learnability
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