Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus

13 December 2023

Papers citing "Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus"

8 / 8 papers shown

Title
Lightweight Trustworthy Distributed Clustering Hongyang Li Caesar Wu Mohammed Chadli Said Mammar Pascal Bouvry 49 0 0 14 Apr 2025
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges Qiongxiu Li Wenrui Yu Yufei Xia Jun Pang FedML 60 1 0 10 Mar 2025
Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study Changlong Ji Stephane Maag Richard Heusdens Qiongxiu Li FedML 34 2 0 21 Sep 2024
Privacy-Preserving Distributed Maximum Consensus Without Accuracy Loss Wenrui Yu Richard Heusdens Jun Pang Qiongxiu Li 28 3 0 16 Sep 2024
AttentionX: Exploiting Consensus Discrepancy In Attention from A Distributed Optimization Perspective Guoqiang Zhang Richard Heusdens 34 0 0 06 Sep 2024
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization Wenrui Yu Qiongxiu Li Milan Lopuhaä-Zwakenberg Mads Græsbøll Christensen Richard Heusdens FedML 38 3 0 12 Jul 2024
Distributed Nonlinear Conic Optimisation with partially separable Structure Richard Heusdens Guoqiang Zhang 44 1 0 15 May 2024
Distributed Optimisation with Linear Equality and Inequality Constraints using PDMM Richard Heusdens Guoqiang Zhang 45 8 0 22 Sep 2023