62 citations · 77 across the 7 of their papers we have counts for
4 papers · 1 filter
Easy Differentially Private Linear Regression
Kareem Amin, Matthew Joseph, Mónica Ribero +1
Linear regression is a fundamental tool for statistical analysis. This has motivated the development of linear regression methods that also satisfy differential privacy and thus gu…
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints
Monica Ribero, Haris Vikalo, Gustavo De Veciana
Federated learning systems facilitate training of global models in settings where potentially heterogeneous data is distributed across a large number of clients. Such systems opera…
Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces
Peter Kairouz, Mónica Ribero, Keith Rush +1
We revisit the problem of empirical risk minimziation (ERM) with differential privacy. We show that noisy AdaGrad, given appropriate knowledge and conditions on the subspace from w…
Communication-Efficient Federated Learning via Optimal Client Sampling
Monica Ribero, Haris Vikalo
Federated learning (FL) ameliorates privacy concerns in settings where a central server coordinates learning from data distributed across many clients. The clients train locally an…