This course will give a detailed introduction to learning theory with a focus on the classification problem. It will be shown how to obtain (pobabilistic) bounds on the generalization error for certain types of algorithms. The main themes will be: * probabilistic inequalities and concentration inequalities * union bounds, chaining * measuring the size of a function class, Vapnik Chervonenkis dimension, shattering dimension and Rademacher averages * classification with real-valued functions Some knowledge of probability theory would be helpful but not required since the main tools will be introduced.
J. Gee. Science Education as a Pathway to Teaching Language Literacy, sense publishers, Rotterdam, https://www.sensepublishers.com/files/9789460911316PR.pdf.(2010)
K. Bruna. Science Education as a Pathway to Teaching Language Literacy, sense publishers, Rotterdam, https://www.sensepublishers.com/files/9789460911316PR.pdf.(2010)
J. Gee. Science Education as a Pathway to Teaching Language Literacy, sense publishers, Rotterdam, https://www.sensepublishers.com/files/9789460911316PR.pdf.(2010)