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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?