The debate was about how much prior structure you need, and what type, not whether you need it. But the answer depends on how much training data you allow yourself to use. The more data you use, the less structure you need. Even convolutional structure can be learned.
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Has anyone learned convolutional structure in a way that generalizes outside the space of training examples? Interested in references.
End of conversation
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