7 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.IR2024
How Powerful is Graph Filtering for Recommendation
Shaowen Peng, Xin Liu, Kazunari Sugiyama +1
It has been shown that the effectiveness of graph convolutional network (GCN) for recommendation is attributed to the spectral graph filtering. Most GCN-based methods consist of a…
cs.IR2024
Privacy-Preserving Sequential Recommendation with Collaborative Confusion
Wei Wang, Yujie Lin, Pengjie Ren +7
Sequential recommendation has attracted a lot of attention from both academia and industry, however the privacy risks associated to gathering and transferring users' personal inter…
cs.IR2022★ 7 cited
SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation
Shaowen Peng, Kazunari Sugiyama, Tsunenori Mine
With the tremendous success of Graph Convolutional Networks (GCNs), they have been widely applied to recommender systems and have shown promising performance. However, most GCN-bas…