315 citations · 370 across the 9 of their papers we have counts for
14 papers
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
We study model personalization under user-level differential privacy (DP) in the shared representation framework. In this problem, there are users whose data is statistically h…
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
Raef Bassily, Cristóbal Guzmán, Michael Menart
In this work, we conduct a systematic study of stochastic saddle point problems (SSP) and stochastic variational inequalities (SVI) under the constraint of -differential pri…
Differentially Private Learning with Margin Guarantees
Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh
We present a series of new differentially private (DP) algorithms with dimension-independent margin guarantees. For the family of linear hypotheses, we give a pure DP learning algo…
Learning from Mixtures of Private and Public Populations
Raef Bassily, Shay Moran, Anupama Nandi
We initiate the study of a new model of supervised learning under privacy constraints. Imagine a medical study where a dataset is sampled from a population of both healthy and unhe…
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán +1
Uniform stability is a notion of algorithmic stability that bounds the worst case change in the model output by the algorithm when a single data point in the dataset is replaced. A…
Private Query Release Assisted by Public Data
Raef Bassily, Albert Cheu, Shay Moran +3
We study the problem of differentially private query release assisted by access to public data. In this problem, the goal is to answer a large class of statistical qu…