7 citations · 14 across the 6 of their papers we have counts for
6 papers
DiffGraph: Heterogeneous Graph Diffusion Model
Zongwei Li, Lianghao Xia, Hua Hua +3
Recent advances in Graph Neural Networks (GNNs) have revolutionized graph-structured data modeling, yet traditional GNNs struggle with complex heterogeneous structures prevalent in…
Out of the Box Thinking: Improving Customer Lifetime Value Modelling via Expert Routing and Game Whale Detection
Shijie Zhang, Xin Yan, Xuejiao Yang +2
Customer lifetime value (LTV) prediction is essential for mobile game publishers trying to optimize the advertising investment for each user acquisition based on the estimated wort…
Federated Unlearning for On-Device Recommendation
Wei Yuan, Hongzhi Yin, Fangzhao Wu +3
The increasing data privacy concerns in recommendation systems have made federated recommendations (FedRecs) attract more and more attention. Existing FedRecs mainly focus on how t…
Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks
Shijie Zhang, Wei Yuan, Hongzhi Yin
In recent years, recommender systems are crucially important for the delivery of personalized services that satisfy users' preferences. With personalized recommendation services, u…
PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
Shijie Zhang, Hongzhi Yin, Tong Chen +3
Due to the growing privacy concerns, decentralization emerges rapidly in personalized services, especially recommendation. Also, recent studies have shown that centralized models a…
Graph Embedding for Recommendation against Attribute Inference Attacks
Shijie Zhang, Hongzhi Yin, Tong Chen +3
In recent years, recommender systems play a pivotal role in helping users identify the most suitable items that satisfy personal preferences. As user-item interactions can be natur…