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* D. Haussler. Probably approximately correct learning. In AAAI-90 Proceedings of the Eight National Conference on Artificial Intelligence, Boston, MA, pages 1101–1108. American Association for Artificial Intelligence, 1990. http://citeseer.ist.psu.edu/haussler90probably.html
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* V. Vapnik and A. Chervonenkis. [https://courses.engr.illinois.edu/ece544na/fa2014/vapnik71.pdf On the uniform convergence of relative frequencies of events to their probabilities]. Theory of Probability and Its Applications, 16(2):264–280, 1971.
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* M. Kearns and [[Leslie Valiant]]. 1989. Cryptographic limitations on learning boolean formulae and finite automata. In Proceedings of the 21st Annual ACM Symposium on Theory of Computing, pages 433–444, New York. ACM. http://citeseer.ist.psu.edu/kearns89cryptographic.html
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* Robert E. Schapire. The strength of weak learnability. Machine Learning, 5(2):197–227, 1990 http://citeseer.ist.psu.edu/schapire90strength.html
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* Blumer, A.; Ehrenfeucht, A.; Haussler, D.; [[Manfred K. Warmuth|Warmuth, M. K.]] [http://www.cse.buffalo.edu/~hungngo/classes/2008/694/papers/occam.pdf Occam's razor] Inf.Proc.Lett. 24, 377–380, 1987.
* Blumer, A.; Ehrenfeucht, A.; Haussler, D.; Warmuth, M. K. [http://www.trhvidsten.com/docs/classics/Blumer-1989.pdf Learnability and the Vapnik-Chervonenkis dimension]. Journal of the ACM, 36(4):929–865, 1989.
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* L. Valiant. [http://www.montefiore.ulg.ac.be/~geurts/Cours/AML/Readings/Valiant.pdf A Theory of the Learnable]. Communications of the ACM, 27(11):1134–1142, 1984.
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A description of some of these publications is given at [[list of important publications in computer science#Machine learning|important publications in machine learning]].
==External links==
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