7 citations · 11 across the 13 of their papers we have counts for
8 papers · 1 filter
Memory-enhanced Invariant Prompt Learning for Urban Flow Prediction under Distribution Shifts
Haiyang Jiang, Tong Chen, Wentao Zhang +4
Urban flow prediction is a classic spatial-temporal forecasting task that estimates the amount of future traffic flow for a given location. Though models represented by Spatial-Tem…
Epidemiology-informed Network for Robust Rumor Detection
Wei Jiang, Tong Chen, Xinyi Gao +3
The rapid spread of rumors on social media has posed significant challenges to maintaining public trust and information integrity. Since an information cascade process is essential…
New Permutation Decomposition Techniques for Efficient Homomorphic Permutation
Xirong Ma, Junling Fang, Chunpeng Ge +5
Homomorphic permutation is fundamental to privacy-preserving computations based on batch-encoding homomorphic encryption. It underpins nearly all homomorphic matrix operations and…
Physics-guided Active Sample Reweighting for Urban Flow Prediction
Wei Jiang, Tong Chen, Guanhua Ye +4
Urban flow prediction is a spatio-temporal modeling task that estimates the throughput of transportation services like buses, taxis, and ride-sharing, where data-driven models have…
A Thorough Performance Benchmarking on Lightweight Embedding-based Recommender Systems
Hung Vinh Tran, Tong Chen, Quoc Viet Hung Nguyen +3
Since the creation of the Web, recommender systems (RSs) have been an indispensable mechanism in information filtering. State-of-the-art RSs primarily depend on categorical feature…
Lightweight Embeddings for Graph Collaborative Filtering
Xurong Liang, Tong Chen, Lizhen Cui +3
Graph neural networks (GNNs) are currently one of the most performant collaborative filtering methods. Meanwhile, owing to the use of an embedding table to represent each user/item…
Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation
Liang Qu, Wei Yuan, Ruiqi Zheng +3
Federated recommender systems (FedRecs) have gained significant attention for their potential to protect user's privacy by keeping user privacy data locally and only communicating…
Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation
Ruiqi Zheng, Liang Qu, Tong Chen +3
In Location-based Social Networks, Point-of-Interest (POI) recommendation helps users discover interesting places. There is a trend to move from the cloud-based model to on-device…