Abhinav Chakraborty

PriME: Privacy-Aware Membership Profile Estimation in Networks

Abstract. This paper presents a novel approach to estimating communbity membership probabilities for network vertices generated by the degree corrected mixed membership stochastic lock model [ 36 ] while preserving individual edge privacy. Operating within the [Formula: see text]...

Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints

This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy constraints. The setting we consider is heterogeneous, encompassing both varying sample sizes and diff...