I've been reading Bengio's tutorial (Learning Deep Architectures for AI), and I'm also going over some reading lists over here (http://www.deeplearning.net/tutorial/).

However, most of them only go as far as 2009, Bengio's paper points out some open questions regarding Deep Nets that might be answered by now.

Other than scanning NIPS and ICML papers, is there any good recent tutorial?

Edit: Bengio answered in G+, and pointed out this paper (http://www.iro.umontreal.ca/~lisa/pointeurs/TPAMISI-2012-04-0260-1.pdf) Any other suggestions are always welcome.

asked Apr 16 '14 at 16:48

Leon%20Palafox's gravatar image

Leon Palafox ♦
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edited Apr 16 '14 at 16:58

I like this talk by Geoff Hinton, which is mostly about the recent paradigm shift from unsupervised pre-training back to purely supervised approaches: https://www.youtube.com/watch?v=vShMxxqtDDs

(Apr 18 '14 at 11:11) Sander Dieleman
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