Search Results for author: Fredrik Harder

Found 1 papers, 0 papers with code

Differentially Private Data Generation Needs Better Features

no code implementations25 May 2022 Fredrik Harder, Milad Jalali Asadabadi, Danica J. Sutherland, Mijung Park

Training even moderately-sized generative models with differentially-private stochastic gradient descent (DP-SGD) is difficult: the required level of noise for reasonable levels of privacy is simply too large.

Transfer Learning

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