Work

Private Sample Alignment for Vertical Federated Learning: An Efficient and Reliable Realization

Year: 2025

Type: article

Source: IEEE Transactions on Information Forensics and Security

DOI: 10.1109/tifs.2025.3555794

Authors: Yuxin Xi, Yu Guo, Shiyuan Xu, Chengjun Cai, Xiaohua Jia

Institutions: Beijing Normal University, University of Hong Kong, City University of Hong Kong, City University of Hong Kong (Dongguan)

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, University Grants Committee, Basic and Applied Basic Research Foundation of Guangdong Province

Awards: G1549391102, G4556148455, G7184951566, G7939304977, G8374877336

OpenAlex ID: W4408971072

FWCI: 2.909

Cites: 49

Cited by: 7

Related to: 10