Computational learning theory: Difference between revisions

Revision as of 21:28, 2 March 2022

Revision as of 23:34, 24 November 2022

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* Exact learning, proposed by [[Dana Angluin]];

* [[Probably approximately correct learning]] (PAC learning), proposed by [[Leslie Valiant]]<ref>{{cite journal |last1=Valiant |first1=Leslie |title=A Theory of the Learnable |journal=Communications of the ACM |date=1984 |volume=27 |issue=11 |pages=1134-1142 |url=https://www.montefiore.ulg.ac.be/~geurts/Cours/AML/Readings/Valiant.pdf |ref=ValTotL}}</ref>;

* [[VC theory]], proposed by [[Vladimir Vapnik]] and [[Alexey Chervonenkis]];

* [[Bayesian inference]];