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cs.LG2022★ 4 cited
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu +6
Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the tw…
cs.LG2020
Active Local Learning
Arturs Backurs, Avrim Blum, Neha Gupta
In this work we consider active local learning: given a query point , and active access to an unlabeled training set , output the prediction of a near-optimal $h \in H…