# Statistical relational learning

## Course info

ICT Doctorate school course page |

## Slides

Graphical models [slides] [handouts] Hidden Markov Models [slides] [handouts] Conditional Random Fields [slides] [handouts] Markov Logic Networks [slides] [handouts] |

## Main references

C.M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006 (esp. chapter 8 on graphical models). L. R. Rabiner A tutorial on Hidden Markov Models and selected applications in speech recognition, Proceedings of the IEEE 77 (2): 257–286, 1989.R. Durbin, S. R. Eddy, A. Krogh, G. Mitchison, Biological Sequence Analysis, Cambridge University Press, 1998.C. Sutton, C., A. McCallum, An Introduction to Conditional Random Fields for Relational Learning, in "Introduction to Statistical Relational Learning", MIT Press, 2006.P. Domingos, S. Kok, D. Lowd, H. Poon, M. Richardson, P. Singla, Markov Logic, in "Probabilistic Inductive Logic Programming", Springer, 2008. |