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great scholars & professors on RBM

已有 3288 次阅读 2013-4-6 08:25 |个人分类:读书日记|系统分类:科研笔记| Learning, deep

(1) Hinton Geoffrey: http://www.cs.toronto.edu/~hinton/

father of RBM, it's him to make the RBM trainable in practice.

(2) Andrew Ng: http://ai.stanford.edu/~ang/

Great professor and great speaker. His student helped to popularize the deep belief network

(3) Honglak Lee: http://web.eecs.umich.edu/~honglak/

It's him to win the best application paper award of ICML 2009. Currently he works on how to model invariance using RBM.

(4) Ruslan Salakhutdinov: http://www.utstat.toronto.edu/~rsalakhu/

He is student of Prof. Hinto,and his major contribution is introduction of deep boltzmann machine. Prof.Hinto coined deep belief network. There two kinds of networks share some similarity, both belonging to deep architectures.

(5) Graham Taylor: http://www.uoguelph.ca/~gwtaylor/

He is also the student of Prof. Hinton, and his major contribution is the introduction of gated boltzmann machine, which makes generate gray scale images possible.

(6) Hugo Larochelle: http://www.dmi.usherb.ca/~larocheh/index_en.html

Again he is Prof. Hinto's student, and his major contribution is applying RBM to model attentionla data.

(7) Mark Ranzato: http://www.cs.toronto.edu/~ranzato/

He finished his Ph.D under Prof. Yann Lecun, and spent two-years' postdoc under Prof. Hinton. His contribution is introduction of one duplicate image to model covariance among neighboring pixels.

(8) Roland Memisevic: http://www.iro.umontreal.ca/~memisevr/

He modeled temporal data using RBM. Now he found a faculty position in the University of Montreal.

(9) Yoshua Bengio: http://www.iro.umontreal.ca/~bengioy/yoshua_en/index.html

Great professor. His work of 'Learning Deep Structure for AI' is a must-read.

(10) Yann Lecun: http://yann.lecun.com/

He is a legend. He disregarded CV guys.He is super smart, and his work may revolutionize object recognition.

(11) Rob Fergus: http://cs.nyu.edu/~fergus/

NYU guy, who rejected when I applied for him. Anyway, a genius, I love him.

(12) Kai Yu: http://www.dbs.ifi.lmu.de/~yu_k/

He inspired me why whitening doesn't make data independent. Sincere thanks to him.


These professor are those who I am most familiar with. However, with emergence of deep belief network and deep boltzmann machine, there are so many other scholars. You may find a list from 2012 UCLA Deep Learning Summer School:

http://www.ipam.ucla.edu/programs/gss2012/






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