36 citations · 81 across the 4 of their papers we have counts for
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cs.LG2019★ 19 cited
Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications
Nicholas Carlini, Úlfar Erlingsson, Nicolas Papernot
We develop techniques to quantify the degree to which a given (training or testing) example is an outlier in the underlying distribution. We evaluate five methods to score examples…
cs.LG2019
That which we call private
Úlfar Erlingsson, Ilya Mironov, Ananth Raghunathan +1
The guarantees of security and privacy defenses are often strengthened by relaxing the assumptions made about attackers or the context in which defenses are deployed. Such relaxati…