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Friday, September 27, 2013

Bayesian non-parametrics idea

 I dont know why but this tutorial is really approachable and makes the idea clear.
Awesome high level overview of bayesian non-parametrics by Zoubin Ghahramani
http://mlg.eng.cam.ac.uk/pub/pdf/Gha12.pdf
https://www.ee.washington.edu/techsite/papers/documents/UWEETR-2010-0006.pdf

 CVPR2012 tutorial applied bayesian non-parametrics
 http://cs.brown.edu/~sudderth/bnpCVPR12/materials.html
 http://cs.brown.edu/~sudderth/bnpCVPR12/resources.html
 http://cs.brown.edu/courses/csci2950-p/lectures.html
http://www.cs.princeton.edu/courses/archive/fall07/cos597C/syllabus.html

Topics in Machine Learning: Bayesian Methods for Machine Learning
http://www.cs.utoronto.ca/~radford/csc2541.S11/ 

http://www.cs.berkeley.edu/~jordan/courses/294-fall09/lectures/nonparametric/

Best place for DP chapter 2 of thesis
http://cs.brown.edu/~sudderth/papers/sudderthPhD.pdf

http://www.cs.toronto.edu/~radford/mixmc.abstract.html
        http://www.cs.toronto.edu/~radford/ftp/bmm.pdf
        http://www.cs.utoronto.ca/~radford/ftp/review.pdf
        http://www.cs.toronto.edu/~radford/ftp/mixmc.pdf
        http://www.cs.toronto.edu/~radford/ftp/mixsplit.pdf
        http://www.cs.berkeley.edu/~jordan/papers/hdp.pdf
        http://books.nips.cc/papers/files/nips18/NIPS2005_0130.pdf
        http://books.nips.cc/papers/files/nips19/NIPS2006_0716.pdf

http://npbayes.wikidot.com/references

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