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The paper characterizes classes of functions for which deep learning can beexponentially better than shallow learning. Deep convolutional networks are aspecial case of these conditions, though weight sharing is not the main reasonfor their exponential advantage.

Why and When Can Deep -- but Not Shallow -- Networks Avoid the Curse of Dimensionality: a Review