1 citations · 2 across the 5 of their papers we have counts for
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cs.IR2023
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…
cs.IR2023★ 1 cited
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…
cs.LG2023★ 1 cited
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…