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stat.ML2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer, Itay Hubara, Daniel Soudry
Background: Deep learning models are typically trained using stochastic gradient descent or one of its variants. These methods update the weights using their gradient, estimated fr…
stat.ML2016
No bad local minima: Data independent training error guarantees for multilayer neural networks
Daniel Soudry, Yair Carmon
We use smoothed analysis techniques to provide guarantees on the training loss of Multilayer Neural Networks (MNNs) at differentiable local minima. Specifically, we examine MNNs wi…