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Saturday, September 21, 2013

Awesome Video Lectures (I liked) @ videolectures.net

Approximate Inference(Expectation Propagation)  by Tom Minka
http://videolectures.net/mlss09uk_minka_ai/#c3275

Topic Models by David Blei
http://videolectures.net/mlss09uk_blei_tm/

Graphical Models and message-passing algorithms by Wainwright
http://videolectures.net/mlss2011_wainwright_messagepassing/

MCMC by murray
http://videolectures.net/mlss09uk_murray_mcmc/

Bayesian Inference and Gaussian Process by Carl Rasmussen
http://videolectures.net/mlss07_rasmussen_bigp/

Structure prediction: A large margin approach by ben taskar
http://videolectures.net/aop07_taskar_pgm/

Algorithms for Predicting Structured Data(OK for beginner, intuitive)
http://videolectures.net/ecmlpkdd2010_gartner_vembu_apsd/

Nonparametric bayesian
http://videolectures.net/mlss2011_teh_nonparametrics/
http://videolectures.net/mlss09uk_teh_nbm/
http://videolectures.net/mlss09uk_orbanz_fnbm/
http://videolectures.net/mlss06au_tresp_dpnbm/

Dirichlet Processes: Tutorial and Practical Course
http://videolectures.net/mlss2012_gorur_dirichlet_practical/
http://videolectures.net/mlss07_teh_dp/

Dimentionality Reduction by Neil Lawrence
http://videolectures.net/mlss2012_lawrence_dimensionality_reduction/

Support Vector Machines
http://videolectures.net/mlss06tw_lin_svm/

Low Rank Modelling by Emmanuel Candes
http://videolectures.net/mlss2011_candes_lowrank/

Geometric Methods and Manifold Learning by Niyogi
http://videolectures.net/mlss09us_niyogi_belkin_gmml/

MAP inference in Discrete Models(Max flow / st cut / submodularity)
http://videolectures.net/bmvc2012_kohli_discrete_models/

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