4 papers
Position: Embodied AI Requires a Privacy-Utility Trade-off
Xiaoliang Fan, Jiarui Chen, Zhuodong Liu +6
Embodied AI (EAI) systems are rapidly transitioning from simulations into real-world domestic and other sensitive environments. However, recent EAI solutions have largely demonstra…
Federated Learning with Domain Shift Eraser
Zheng Wang, Zihui Wang, Xiaoliang Fan +1
Federated learning (FL) is emerging as a promising technique for collaborative learning without local data leaving their devices. However, clients' data originating from diverse do…
P4GCN: Vertical Federated Social Recommendation with Privacy-Preserving Two-Party Graph Convolution Network
Zheng Wang, Wanwan Wang, Yimin Huang +5
In recent years, graph neural networks (GNNs) have been commonly utilized for social recommendation systems. However, real-world scenarios often present challenges related to user…
Federated Graph Learning for Cross-Domain Recommendation
Ziqi Yang, Zhaopeng Peng, Zihui Wang +6
Cross-domain recommendation (CDR) offers a promising solution to the data sparsity problem by enabling knowledge transfer across source and target domains. However, many recent CDR…