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Hongquan Liu

2 accepted papers

2026

FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments

ICLR 2026poster

Semi-supervised federated learning (SSFL) has emerged as an effective approach to leverage unlabeled data distributed across multiple data owners for improving model generalization. Existing SSFL methods typically assume that labeled and unlabeled data share the same label space. However, in realist…

Cited by 0SourcecodeScholar
2026

Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients

ICML 2026poster

In this paper, we present a novel federated independence testing method that addresses both theoretical and practical challenges arising from client heterogeneity. We begin by revisiting existing federated independence testing methods and showing why they fail to provide valid guarantees or maintain…

Cited by 0SourceScholar