Web: http://arxiv.org/abs/2206.05794

Sept. 29, 2022, 1:13 a.m. | Tomer Galanti, Zachary S. Siegel, Aparna Gupte, Tomaso Poggio

stat.ML updates on arXiv.org arxiv.org

We analyze deep ReLU neural networks trained with mini-batch Stochastic
Gradient Descent (SGD) and weight decay. We show, both theoretically and
empirically, that when training a neural network using SGD with weight decay
and small batch size, the resulting weight matrices tend to be of small rank.
Our analysis relies on a minimal set of assumptions; the neural networks may be
arbitrarily wide or deep and may include residual connections, as well as
convolutional layers. The same analysis implies the …

arxiv bias low networks neural networks

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