Search results with tag "Deep learning requires"

Understanding deep learning requires rethinking …

to Livni et al. (2014) achieved a similar result with far more parameters, namely, O (dn ): While our depth 2 network inevitably has large width, we can also come up with a depth k network in which each layer has only O (n=k ) parameters. While prior expressivity results focused on what functions neural nets can represent over the entire

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