Another way to divide and conquer
	• Re-representing the data: Each time the base learner is called, it passes a transformed version of the data to the next learner. – Can we learn a deep, dense DAG one layer at a time, starting at the bottom, and still guarantee that learning each layer improves the overall model of the training data? • This seems very unlikely. Surely we need to know the weights in higher layers to learn lower layers?