19 citations · 63 across the 17 of their papers we have counts for
10 papers · 1 filter
Private Isotonic Regression
Badih Ghazi, Pritish Kamath, Ravi Kumar +1
In this paper, we consider the problem of differentially private (DP) algorithms for isotonic regression. For the most general problem of isotonic regression over a partially order…
Logarithmic Regret from Sublinear Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We consider the online linear optimization problem, where at every step the algorithm plays a point in the unit ball, and suffers loss for some cost…
Large-Scale Differentially Private BERT
Rohan Anil, Badih Ghazi, Vineet Gupta +2
In this work, we study the large-scale pretraining of BERT-Large with differentially private SGD (DP-SGD). We show that combined with a careful implementation, scaling up the batch…
Deep Learning with Label Differential Privacy
Badih Ghazi, Noah Golowich, Ravi Kumar +2
The Randomized Response (RR) algorithm is a classical technique to improve robustness in survey aggregation, and has been widely adopted in applications with differential privacy g…
Sample-efficient proper PAC learning with approximate differential privacy
Badih Ghazi, Noah Golowich, Ravi Kumar +1
In this paper we prove that the sample complexity of properly learning a class of Littlestone dimension with approximate differential privacy is , ignoring priva…
Robust and Private Learning of Halfspaces
Badih Ghazi, Ravi Kumar, Pasin Manurangsi +1
In this work, we study the trade-off between differential privacy and adversarial robustness under L2-perturbations in the context of learning halfspaces. We prove nearly tight bou…