3 papers
eess.SP2026
When Is Distributed Nonlinear Aggregation Private? Optimality and Information-Theoretical Bounds
Wenrui Yu, Jaron Skovsted Gundersen, Richard Heusdens +1
Nonlinear aggregation is central to modern distributed systems, yet its privacy behavior is far less understood than that of linear aggregation. Unlike linear aggregation where mat…
eess.SP2025
Optimal Privacy-Preserving Distributed Median Consensus
Wenrui Yu, Qiongxiu Li, Richard Heusdens +1
Distributed median consensus has emerged as a critical paradigm in multi-agent systems due to the inherent robustness of the median against outliers and anomalies in measurement. D…
cs.LG2024
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
Wenrui Yu, Qiongxiu Li, Milan Lopuhaä-Zwakenberg +2
Federated learning (FL) emerged as a paradigm designed to improve data privacy by enabling data to reside at its source, thus embedding privacy as a core consideration in FL archit…