This paper proposes a privacy-preserving approach for learning effective personalized models on distributed user data while guaranteeing the differential�...

Jul 17, 2023 � We propose Privacy-preserving Community-Based Federated machine Learning (PCBFL), a novel Clustered FL framework that can cluster patients using patient-level�...

We have considered privacy in the ( , δ)-differential privacy model and provided a privacy-preserving algorithms for the personalized federated learning. We�...

Jan 30, 2024 � We propose privacy-preserving and personalized federated learning, a unified federated learning framework to simultaneously address privacy preservation and�...

This paper proposes a privacy- preserving approach for learning effective personalized models on distributed user data while guaranteeing the differential�...

Sep 13, 2024 � PPFL is a personalized federated algorithm for heterogeneously distributed clients that expands the feature space for client-specific vertical feature�...

3 days ago � In this paper, we propose a generative attack method based on conditional generative models to reveal the potential risk empirically.

Aug 29, 2022 � In this paper, we propose FedEgo, a federated graph learning framework based on ego-graphs to tackle the challenges above.

Nov 13, 2023 � In this article, we propose FedEgo, a federated graph learning framework based on ego-graphs to tackle the challenges above.

Dec 7, 2023 � This blog series focuses on federated learning, an approach that addresses the fundamental privacy challenge of traditional machine learning.