73 citations · 585 across the 58 of their papers we have counts for
3 papers · 2 filters
Differentially Private Fair Learning
Matthew Jagielski, Michael Kearns, Jieming Mao +4
Motivated by settings in which predictive models may be required to be non-discriminatory with respect to certain attributes (such as race), but even collecting the sensitive attri…
The Limits of Post-Selection Generalization
Kobbi Nissim, Adam Smith, Thomas Steinke +2
While statistics and machine learning offers numerous methods for ensuring generalization, these methods often fail in the presence of adaptivity---the common practice in which the…
Local Differential Privacy for Evolving Data
Matthew Joseph, Aaron Roth, Jonathan Ullman +1
There are now several large scale deployments of differential privacy used to collect statistical information about users. However, these deployments periodically recollect the dat…