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Poster

Exploring Generalization in Deep Learning

Behnam Neyshabur · Srinadh Bhojanapalli · David Mcallester · Nati Srebro

Pacific Ballroom #142

Keywords: [ Deep Learning ]


Abstract:

With a goal of understanding what drives generalization in deep networks, we consider several recently suggested explanations, including norm-based control, sharpness and robustness. We study how these measures can ensure generalization, highlighting the importance of scale normalization, and making a connection between sharpness and PAC-Bayes theory. We then investigate how well the measures explain different observed phenomena.

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