most citedFedMCSA: Personalized Federated Learning via Model Components Self-Attention

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024

Contribution Evaluation of Heterogeneous Participants in Federated Learning via Prototypical Representations

Qi Guo, Minghao Yao, Zhen Tian +4

Contribution evaluation in federated learning (FL) has become a pivotal research area due to its applicability across various domains, such as detecting low-quality datasets, enhan…

cs.CR2024

SecGraph: Towards SGX-based Efficient and Confidentiality-Preserving Graph Search

Qiuhao Wang, Xu Yang, Saiyu Qi +1

Graphs have more expressive power and are widely researched in various search demand scenarios, compared with traditional relational and XML models. Today, many graph search servic…

cs.LG2022★ 1 cited

FedMCSA: Personalized Federated Learning via Model Components Self-Attention

Qi Guo, Yong Qi, Saiyu Qi +2

Federated learning (FL) facilitates multiple clients to jointly train a machine learning model without sharing their private data. However, Non-IID data of clients presents a tough…