12 citations · 25 across the 16 of their papers we have counts for
Showing 2026 · cs.CRShow all
2 papers · 2 filters
cs.CR2026
PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning
Harsh Kasyap, Anil Kumar Pradhan, Ugur Ilker Atmaca +2
Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing user privacy. However, traditiona…
cs.CR2026
Differentially Private Hierarchical Heavy Hitters
Ari Biswas, Graham Cormode, Yaron Kanza +2
The task of finding _Hierarchical_ Heavy Hitters (HHH) was introduced by Cormode et al. [VLDB 2003] as a generalisation of the heavy hitter problem. While finding HHH in data strea…