What We Saw (and Liked) in 2017

In the current era of Deep Learning, we can legitimately ask ourselves whether this debate still makes sense for this kind of models. The work of Sun et al. (Google) addresses this question by training a deep neural network with an unprecedented amount of data (300...

What We Saw (and Liked) in 2017

In the current era of Deep Learning, we can legitimately ask ourselves whether this debate still makes sense for this kind of models. The work of Sun et al. (Google) addresses this question by training a deep neural network with an unprecedented amount of data (300...

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