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An Opinionated Introduction to AutoML and Neural Architecture Search

http://www.fast.ai/2018/07/16/auto-ml2/
Deep learning holds many mysteries for theory, as we have discussed on this blog. Lately many ML theorists have become interested in the generalization mystery: why do trained deep nets perform well on previously unseen data, even though they have way more free parameters than the number of datapoints (the classic “overfitting” regime)?

http://www.offconvex.org/2017/12/08/generalization1/