Added multiplicative filtering, a generalization of dropout
MNIST, 400 units, elastic net scaling 0.25, 10% dropout,
encoder row init 0.8, 11 ista iterations, 1 regularization iterations,
class rows norm 5, encoder rows norms 1.25,
learning rate 5e-3, minibatch size 10, 100 epochs pretraining
decoding_feature_extraction_dictionary rows are fully normalized