463 citations · 1.5k across the 100 of their papers we have counts for
121 papers
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Hechuan Wen, Tong Chen, Li Kheng Chai +3
Due to the imbalanced nature of networked observational data, the causal effect predictions for some individuals can severely violate the positivity/overlap assumption, rendering u…
Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation
Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen +2
Latent factor models are the dominant backbones of contemporary recommender systems (RSs) given their performance advantages, where a unique vector embedding with a fixed dimension…
Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation
Guanhua Ye, Tong Chen, Quoc Viet Hung Nguyen +1
As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model, personalized IoT service providers ha…
Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation
Xin Xia, Junliang Yu, Guandong Xu +1
On-device recommender systems recently have garnered increasing attention due to their advantages of providing prompt response and securing privacy. To stay current with evolving u…
Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph
Yi Liu, Hongrui Xuan, Bohan Li +3
Knowledge graphs (KGs) are commonly used as side information to enhance collaborative signals and improve recommendation quality. In the context of knowledge-aware recommendation (…
Graph Condensation for Inductive Node Representation Learning
Xinyi Gao, Tong Chen, Yilong Zang +4
Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. T…