34 citations · 77 across the 11 of their papers we have counts for
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cs.IR2021★ 34 cited
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
Kelong Mao, Jieming Zhu, Xi Xiao +3
With the recent success of graph convolutional networks (GCNs), they have been widely applied for recommendation, and achieved impressive performance gains. The core of GCNs lies i…
cs.IR2021★ 22 cited
SimpleX: A Simple and Strong Baseline for Collaborative Filtering
Kelong Mao, Jieming Zhu, Jinpeng Wang +4
Collaborative filtering (CF) is a widely studied research topic in recommender systems. The learning of a CF model generally depends on three major components, namely interaction e…
cs.LG2021★ 3 cited
Learnable Hypergraph Laplacian for Hypergraph Learning
Jiying Zhang, Yuzhao Chen, Xi Xiao +2
Hypergraph Convolutional Neural Networks (HGCNNs) have demonstrated their potential in modeling high-order relations preserved in graph-structured data. However, most existing conv…