Towards moderate overparameterization: global convergence guarantees for training shallow neural networks

12 Feb 2019Samet OymakMahdi Soltanolkotabi

Many modern neural network architectures are trained in an overparameterized regime where the parameters of the model exceed the size of the training dataset. Sufficiently overparameterized neural network architectures in principle have the capacity to fit any set of labels including random noise... (read more)

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