Tutorials on topics in machine learning
http://nips.cc/Conferences/2007/Program/event.php?ID=575
http://cmp.felk.cvut.cz/~sochmj1/adaboost_talk.pdf
http://videolectures.net/mlss05us_schapire_b/
http://www.cs.princeton.edu/~schapire/boost.html
http://en.wikipedia.org/wiki/AdaBoost
http://www.inf.fu-berlin.de/inst/ag-ki/adaboost4.pdf
http://atpassos.posterous.com/pegasos-in-python-0
http://www.cse.ohio-state.edu/~satuluri/research.html
This technique was used to calculate pairwise similarity in this paper Local Graph Sparsification. The code implements minwise hashing.
message passing
http://www.eecs.berkeley.edu/~wainwrig/icml08/tutorial_icml08.html
http://videolectures.net/kdd2010_banerjee_igmdm/
http://pages.cs.wisc.edu/~beechung/icml11-tutorial/
competive collaborative filtering
http://www.math.tau.ac.il/~mansour/ml-course-10/students_projects/document.pdf
http://users.cs.fiu.edu/~taoli/pub/p125-li-sigir2011.pdf
http://videolectures.net/kdd2010_papadimitriou_sun_yan_lsdm/
svm: http://videolectures.net/mlss06tw_lin_svm/
http://scikit-learn.sourceforge.net/stable/index.html
graphical model: Course http://www-users.cs.york.ac.uk/jc/teaching/agm/
video: graphical model http://videolectures.net/mlss05au_roweis_pgm/
http://videolectures.net/mlss06tw_roweis_mlpgm/
video: adPredictor, matchbox
http://videolectures.net/ecmlpkdd2010_graepel_mlm/
http://videolectures.net/socialweb2011_gael_social/
tutorial videos, slides and papers:
http://videolectures.net/mlss07_rasmussen_bigp/
http://videolectures.net/epsrcws08_rasmussen_lgp/
http://videolectures.net/gpip06_mackay_gpb/
http://videolectures.net/gpip06_bletchley_park/
http://www.eurandom.nl/events/workshops/2010/YESIV/Prog-Abstr_files/Ghahramani-lecture2.pdf
http://mlg.eng.cam.ac.uk/tutorials/06/es.pdf
http://www.cs.ubc.ca/~hutter/earg/papers05/rasmussen_gps_in_ml.pdf
http://learning.eng.cam.ac.uk/carl/talks/gpnt06.pdf
http://www.gaussianprocess.org/
http://www.gaussianprocess.org/gpml/