MetaInit: Initializing learning by learning to initialize

NeurIPS 2019 Yann N. DauphinSamuel Schoenholz

Deep learning models frequently trade handcrafted features for deep features learned with much less human intervention using gradient descent. While this paradigm has been enormously successful, deep networks are often difficult to train and performance can depend crucially on the initial choice of parameters... (read more)

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