MIG1001 | Stochastic Modeling of Data |
Teaching Staff in Charge |
Assoc.Prof. CSATO Lehel, Ph.D., csatolcs.ubbcluj.ro |
Aims |
References |
[1]. Russell S, Norvig P. (2003) Artificial Intelligence: A Modern Approach (Second Edition), Prentice Hall.
[2]. Mitchell T (1997) Machine Learning, McGraw Hill. [3]. Bernardo J.M, Smith A.F.M (2000) Bayesian Theory, John Wiley & Sons. [4]. MacKay D.J.C (2003) Information Theory, Inference and Learning Algorithms, Cambridge University Press, HTTP: http://wol.ra.phy.cam.ac.uk/mackay/itila/book.html. [5]. Rasmussen C.E, Williams C.K.I (2006) Gaussian Processes for Machine Learning, The MIT Press. [6]. Rabiner L.R, Juang, B.H (1986) An introduction to Hidden Markov models, IEEE ASSP Magazine, pp: 4-15. [7]. Durbin R, Eddy S.R, Krogh A, Mitchison G (1999) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press. [8]. Hyvärinen A, Karhunen J, Oja E (2001) Independent Component Analysis, Wiley-Interscience. [9]. Barto A. (2002): Statistical Pattern Recognition, John Wiley & Sons. |
Assessment |
Links: | Syllabus for all subjects Romanian version for this subject Rtf format for this subject |