Q:

Fast algorithms to train a perceptron / neural network / ANN

Can anyone provide a brief overview of the most popular training algorithms for perceptrons?
I am currently training my perceptron using standard stochastic gradient descent (online gradient descent) with a fixed learning rate.
There seems to be hundreds of different algorithms which claim to perform better, but I have found it difficult to find out which one would be most promising to implement (with complexity and time to code up/understand being costs).
Also, I am using theano on python.

A:

I'd like to thank everyone for their answers and recommend the following paper to anyone trying to answer a similar question:
Efficient Backprop:
http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf

