39 citations · 47 across the 2 of their papers we have counts for
2 papers
cs.CR2020★ 8 cited
Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent
Shuang Song, Thomas Steinke, Om Thakkar +1
We revisit the well-studied problem of differentially private empirical risk minimization (ERM). We show that for unconstrained convex generalized linear models (GLMs), one can obt…
cs.DS2017★ 39 cited
Practical Locally Private Heavy Hitters
Raef Bassily, Kobbi Nissim, Uri Stemmer +1
We present new practical local differentially private heavy hitters algorithms achieving optimal or near-optimal worst-case error and running time -- TreeHist and Bitstogram. In bo…