In the past decade or so, (deep) neural networks have captured people’s imagination through their empirical success in learning problems involving real-world high-dimensional data such as images, speech, and text [LBH15]. Nevertheless, there is quite a bit of mystery as to how deep networks achieve such striking results. Modern deep networks are typically designed through trial and error.
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