1 citations · 2 across the 5 of their papers we have counts for
5 papers
Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection
Hung Vinh Tran, Tong Chen, Hechuan Wen +3
Content-based recommendation systems (CRSs) utilize content features to predict user-item interactions, serving as essential tools for helping users navigate information-rich web s…
RobGC: Towards Robust Graph Condensation
Xinyi Gao, Hongzhi Yin, Tong Chen +3
Graph neural networks (GNNs) have attracted widespread attention for their impressive capability of graph representation learning. However, the increasing prevalence of large-scale…
On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm
Hongzhi Yin, Tong Chen, Liang Qu +1
Given the sheer volume of contemporary e-commerce applications, recommender systems (RSs) have gained significant attention in both academia and industry. However, traditional clou…
Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks
Zongwei Wang, Junliang Yu, Min Gao +3
Contrastive learning (CL) has recently gained prominence in the domain of recommender systems due to its great ability to enhance recommendation accuracy and improve model robustne…
Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation
Xinyi Gao, Wentao Zhang, Junliang Yu +4
Graph neural networks (GNNs) have exhibited exceptional efficacy in a diverse array of applications. However, the sheer size of large-scale graphs presents a significant challenge…