Sunday, March 13, 2016

Nobody in the world knows how to train one hidden layer

I said it.
In recent years, there has been a lot of buzz about deep learning, where the learning algorithm is not based on the Bayes rule and probability. People are optimizing arbitrary, complicated cost functions, and they are doing it with gradient descent, so they don't even reach the minimum of the (incorrect) function that they want to optimize.
I just wanted to remind that nobody in the world knows how to train one hidden layer well, so perhaps instead of hand-waving about deep learning that much, which gets annoying, it may be worth to examine again simpler, fundamental models.

My publication on the Netflix Prize is now free. Download it here.
The previous 4-page publication has so far over 450 citations, and the newer publication has 195 pages and 0 citations.

So read it, cite it. My h-index is 1, and I want to increase it to 2. I don't feel like a real scientist with an h-index 1.

You have to read it to not stay behind your competition.

3 comments:

Anonymous said...

This is simply not true.

ap said...

It's good that it isn't not true in a complicated way.

Anonymous said...

Trust me, it's not true in a bad way.