mPL measures attacker-aligned privacy leakage from joint data releases and AmPL provides an adaptive way to bound it with low utility cost in ML settings.
2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS) , pages=
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Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption
mPL measures attacker-aligned privacy leakage from joint data releases and AmPL provides an adaptive way to bound it with low utility cost in ML settings.