4 citations · 5 across the 8 of their papers we have counts for
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cs.LG2024
Forgetting Through Transforming: Enabling Federated Unlearning via Class-Aware Representation Transformation
Qi Guo, Zhen Tian, Minghao Yao +4
Federated Unlearning (FU) enables clients to selectively remove the influence of specific data from a trained federated learning model, addressing privacy concerns and regulatory r…
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…