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author = Haussler, David (6 entries)  Select: All None   Action: Show BibTeX

David Haussler. 1990. Probably Approximately Correct Learning. In National Conference on Artificial Intelligence, pp 1101--1108, May. [ML] google scholar
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler and Manfred K. Warmuth. 1989. Learnability and the Vapnik-Chervonenkis Dimension. Journal of the ACM, vol 36, no 4, pp 929--965, October. ACM Press. [ML] google scholar
Eric B. Baum and David Haussler. 1989. What Size Net Gives Valid Generalization?. Neural Computation, vol 1, pp 151--160. Massachussets Institute of Technology. [ML] google scholar
David Haussler, Nick Littlestone and Manfred K. Warmuth. 1988. Predicting $(0, 1)$-Functions on Randomly Drawn Points. In 29th Annual Symposium on Foundations of Computer Science, pp 100--109, October. [ML] google scholar
David Haussler. 1988. Quantifying inductive bias: AI learning algorithms and Valiant's learning framework. Artificial Intelligence, vol 36, pp 177-221. Reprint:Shavlik & Dietterich, Readings in ML, 1990. [AI] google scholar
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler and Manfred K. Warmuth. 1987. Occam's Razor. Information Processing Letters, vol 24, pp 377--380. Elsevier Science Publishers. [ML] google scholar

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