I am trying to implement convolutional neural network by Lecun. I have two questions. 1) Do i have to multiply activation function on the (max_value * weight_value) in the maxpooling layer. 2) if yes than in backpropagating the error as i selected only one value from 2x2 receptive field. How can i distribute the error for the other 3 values in the receptive field. Should i replicate one error for all 2x2 window. 3) If no than in backpropagation How can i take determinant of the output i.e. (x*(1-x)? As to find gradient, we need derivative of the activated weighted sum i.e f'(x) 4) USing stochastic diagonal livenberg marquardt method, What should i take the value for eeta, and meeo in equation (21) page 2319 of Lecun Paper http://enpub.fulton.asu.edu/cseml/summer08/papers/cnn-appendix.pdf
I will be thankful for any explanation, or code sample etc. Regards