[acqq]

The most interesting bit for me is at the end of another blog entry:

http://blogs.technet.com/b/inside_microsoft_research/archive...

"An intern at Microsoft Research Redmond, George Dahl, now at the University of Toronto,

http://www.cs.toronto.edu/~gdahl/

contributed insights into the working of DNNs and experience in training them. His work helped Yu and teammates produce a paper called Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition.

http://research.microsoft.com/pubs/144412/DBN4LVCSR-TransASL...

In October 2010, Yu presented the paper during a visit to Microsoft Research Asia. Seide was intrigued by the research results, and the two joined forces in a collaboration that has scaled up the new, DNN-based algorithms to thousands of hours of training data."

[gdahl]

For people interested in some (currently) undocumented research code in python implementing DNNs that is also on my website. Although the code is only an initial release. I will improve it later, but if I waited until it wasn't embarrassing I would never release it, so I just posted it.

[pathdependent]

Thank you for doing so!

Overwhelmingly, it is my experience that researchers in computational disciplines publish papers with half-finished code "available on request" -- and requests are often ignored. It's refreshing to hear someone say, "Yes, the code needs work, but it should be available."