3 papers
cs.IT2026
Information-Theoretic Secure Aggregation over Regular Graphs
Xiang Zhang, Zhou Li, Han Yu +4
Large-scale decentralized learning frameworks such as federated learning (FL), require both communication efficiency and strong data security, motivating the study of secure aggreg…
cs.IT2026
Optimal Rate Region for Multi-server Secure Aggregation with User Collusion
Zhou Li, Xiang Zhang, Kai Wan +3
Secure aggregation is a fundamental primitive in privacy-preserving distributed learning systems, where an aggregator aims to compute the sum of users' inputs without revealing ind…
cs.IT2025
Fundamental Limits of Hierarchical Secure Aggregation with Cyclic User Association
Xiang Zhang, Zhou Li, Kai Wan +3
Secure aggregation is motivated by federated learning (FL) where a cloud server aims to compute an {aggregated} model (i.e., weights of deep neural networks) of the locally-trained…