Enhancing Data Provenance and Model Transparency in Federated Learning Systems — A Database Approach
Authors: Michael Gu, Ramasoumya Naraparaju, Dongfang Zhao | Published: 2024-03-03
連合学習
Analysis of Privacy Leakage in Federated Large Language Models
Authors: Minh N. Vu, Truc Nguyen, Tre' R. Jeter, My T. Thai | Published: 2024-03-02
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach
Authors: Qi Tan, Qi Li, Yi Zhao, Zhuotao Liu, Xiaobing Guo, Ke Xu | Published: 2024-03-02
Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs
Authors: Anika Hannemann, Jan Ewald, Leo Seeger, Erik Buchmann | Published: 2024-02-22
Federated Bayesian Network Ensembles
Authors: Florian van Daalen, Lianne Ippel, Andre Dekker, Inigo Bermejo | Published: 2024-02-19
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets
Authors: Irina Arévalo, Jose L. Salmeron | Published: 2024-02-15
FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning
Authors: Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos, Antonio Skarmeta | Published: 2024-02-15
An advanced data fabric architecture leveraging homomorphic encryption and federated learning
Authors: Sakib Anwar Rieyan, Md. Raisul Kabir News, A. B. M. Muntasir Rahman, Sadia Afrin Khan, Sultan Tasneem Jawad Zaarif, Md. Golam Rabiul Alam, Mohammad Mehedi Hassan, Michele Ianni, Giancarlo Fortino | Published: 2024-02-15
FedSiKD: Clients Similarity and Knowledge Distillation: Addressing Non-i.i.d. and Constraints in Federated Learning
Authors: Yousef Alsenani, Rahul Mishra, Khaled R. Ahmed, Atta Ur Rahman | Published: 2024-02-14
FedMIA: An Effective Membership Inference Attack Exploiting “All for One” Principle in Federated Learning
Authors: Gongxi Zhu, Donghao Li, Hanlin Gu, Yuan Yao, Lixin Fan, Yuxing Han | Published: 2024-02-09 | Updated: 2025-03-27