136 citations · 249 across the 7 of their papers we have counts for
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cs.IR2021★ 136 cited
Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation
Junwei Zhang, Min Gao, Junliang Yu +3
With the prevalence of social media, there has recently been a proliferation of recommenders that shift their focus from individual modeling to group recommendation. Since the grou…
cs.LG2021
Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack
Fan Wu, Min Gao, Junliang Yu +3
To explore the robustness of recommender systems, researchers have proposed various shilling attack models and analyzed their adverse effects. Primitive attacks are highly feasible…
cs.IR2021★ 10 cited
Socially-Aware Self-Supervised Tri-Training for Recommendation
Junliang Yu, Hongzhi Yin, Min Gao +3
Self-supervised learning (SSL), which can automatically generate ground-truth samples from raw data, holds vast potential to improve recommender systems. Most existing SSL-based me…