|
Machine Learning II (2007/2008)5/16 Computational Learning TheoryIn this overview lecture of computational learning theory we discuss such classical topics as learning boolean functions, decision lists and half planes in n-dimensional Euclidean space. We describe the PAC model and the online learning model and end with an introduction to VC theory. Concepts covered: Non-probabilistic approaches to learning, online learning and PAC learning. Learning conjunctions, disjunctions and decision lists. The eliminiation algorithm, winnow, the weighted majority algorithm and the perceptron. Growth function and Vapnik-Chervonenkis dimension.
Slides available [here] |