tutorial ml codes

gistfile1.md

General

Tutorials on topics in machine learning

Hashing Searching Sketching.

Parallel Machine Learning

http://graphlab.org/

AdaBoost

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

sdpy:python impl

icsi impl

Stochastic Gradient Descent (Pegasos for SVM)

http://atpassos.posterous.com/pegasos-in-python-0

Bayes LSH

http://www.cse.ohio-state.edu/~satuluri/research.html

Minwise Hashing

This technique was used to calculate pairwise similarity in this paper Local Graph Sparsification. The code implements minwise hashing.

Graph Clustering

GraClus

Metis+MQI

MLR+MCL

Lectures on clustering

Ensemble Learning

tutorial

slides

message passing

message passing

http://www.eecs.berkeley.edu/~wainwrig/icml08/tutorial_icml08.html

http://videolectures.net/kdd2010_banerjee_igmdm/

bandit problem

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

large scale data mining

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/

Gaussian Process

tutorial videos, slides and papers:

videos:

http://videolectures.net/mlss07_rasmussen_bigp/

http://videolectures.net/epsrcws08_rasmussen_lgp/

http://videolectures.net/gpip06_mackay_gpb/

http://videolectures.net/gpip06_bletchley_park/

lectures

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/

http://people.ee.duke.edu/~lcarin/David1.27.06.pdf

phd thesis:Gaussian Process Model

Great!