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Contributed talk 1 - A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
Behnam Neyshabur

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Behnam Neyshabur (New York University)

I am a staff research scientist at Google. Before that, I was a postdoctoral researcher at New York University and a member of Theoretical Machine Learning program at Institute for Advanced Study (IAS) in Princeton. In summer 2017, I received a PhD in computer science at TTI-Chicago where I was fortunate to be advised by Nati Srebro.

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