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Friday, April 17, 2015

From reproduction of research to original research

I am at a decision point concerning my next time investment.

By modding Andrea's code and getting decent scores for in a few minutes for the MNIST examples, I believe I've confirmed that I can use my laptop to do neural net work at the state of the art 15 years ago. At this point I'm basically back to where I was when I finished my PhD.

I could now move from the antiquated and simple FANN shallow net framework to a more sophisticated environment like Theano, Pylearn2, Torch or Caffe, and tackle harder problems with more recent methods. 

However I'm afraid of two things:
  • A slow learning curve as I wade my way through a novel programming environment.
  • Inadequate computational resources: my laptop vs. multi-GPU clusters at Google and M$.  I am competing with clusters that are 3 orders of magnitude faster. 
The alternatives are thus to either learn modern methods and locate some powerful equipment —eg. an Amazon AWS instance with a GPU—  or to think up some original contributions which can be usefully demonstrated with an old set of tools and benchmarks.

Comments are welcome. 

Edmund

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