| 01. Bishop, Pattern Recognition and Machine Learning, Springer-Verlag, 2006. (recommended) |
| 02. Duda, Hart, Stock, Pattern Classification, Wiley, 2000. (recommended) |
| 03. Haykin, Neural Networks, Prentice Hall, 1998. (recommended) |
| 04. Kohonen, Self-Organizing Maps, Springer-Verlag, 1997. (recommended) |
| 05. Schölkopf, Smola, Learning with Kernels, MIT Press, 2002. (recommended) |
| 06. Russel, Norvig, Artificial Intelligence, Prentice Hall, 2003, Chapters 13 and 14. (recommended) |
| 07. Cichocki, Amari, Adaptive Blind Signal and Image Processing, Wiley, 2002. (additional) |
| 08. Cowell, Dawid, Lauritzen, Spiegelhalter, Probabilistic Networks and Expert Systems, Springer Verlag, 1999. (additional) |
| 09. Hyvärinen, Karhunen, Oja, Independent Component Analysis, Wiley, 2001. (additional) |
| 10. Jordan (Editor), Learning in Graphical Models, MIT Press, 1999. (additional) |
| 11. Kay, Fundamentals of Statistical Signal Processing - Vol. I: Estimation Theory, Prentice Hall, 1993. (additional) |
| 12. Ripley, Pattern Recognition and Neural Networks, Cambridge University Press, 1996. (additional) |
| 13. Vapnik, Statistical Learning Theory, Wiley, 1998. (additional) |
| One or two specific book chapters are assigned / recomended to every topic of the lecture. This list of recommendations is explained during the first class of every module component and is available via TU Berlin’s ISIS platform |
