16 citations · 31 across the 6 of their papers we have counts for
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cs.IR2021★ 1 cited
How Powerful is Graph Convolution for Recommendation?
Yifei Shen, Yongji Wu, Yao Zhang +4
Graph convolutional networks (GCNs) have recently enabled a popular class of algorithms for collaborative filtering (CF). Nevertheless, the theoretical underpinnings of their empir…
cs.IR2021★ 16 cited
Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation
Yongji Wu, Defu Lian, Neil Zhenqiang Gong +4
Self-attention has become increasingly popular in a variety of sequence modeling tasks from natural language processing to recommendation, due to its effectiveness. However, self-a…
cs.IR2021★ 6 cited
Rethinking Lifelong Sequential Recommendation with Incremental Multi-Interest Attention
Yongji Wu, Lu Yin, Defu Lian +4
Sequential recommendation plays an increasingly important role in many e-commerce services such as display advertisement and online shopping. With the rapid development of these se…