This page will be updated during the term.

Textbooks for CS 830

The course does not follow any textbook. Textbooks and monographs of interest:

M.J. Kearns, U.V. Vazirani, An Introduction to Computational Learning Theory, MIT Press 1994.
(PAC learning)

S. Ben-David, S. Shalev-Shwartz, Introduction to Machine Learning, Lecture Notes 2010, available here

T.M. Mitchell, Machine Learning, McGraw Hill 1997.
(ML in general)

C.M. Bishop, Pattern Recognition and Machine Learning, Springer 2006.
(ML in general)

N. Cristianini, J. Shawe-Taylor, An Introduction to Support Vector Machines, Cambridge University Press 2000.
(Support Vector Machines)

Other background material for CS 830

D. Angluin. Queries and Concept Learning. Machine Learning, 2(4):319-342, 1988.
(Learning from queries)

A. Blumer, A. Ehrenfeucht, D. Haussler, M.K. Warmuth. Learnability and the Vapnik-Chervonenkis dimension. Journal of the ACM, 36(4):929-965, 1989.
(PAC learning)

L. Valiant. A theory of the learnable. Communications of the ACM, 27(11):1134-1142, 1984.
(PAC learning)

V. Vapnik, A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications, 16(2):264-280, 1971.
(VC dimension)
 
design: raura