3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.LG2020
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…
cs.LG2020
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…
cs.IR2020★ 3 cited
Federating Recommendations Using Differentially Private Prototypes
Mónica Ribero, Jette Henderson, Sinead Williamson +1
Machine learning methods allow us to make recommendations to users in applications across fields including entertainment, dating, and commerce, by exploiting similarities in users'…