activity
20142020
most citedHierarchical Graph Pooling with Structure Learning

119 citations · 153 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2020

Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback

Jiawei Chen, Can Wang, Sheng Zhou +4

Recommendation from implicit feedback is a highly challenging task due to the lack of the reliable observed negative data. A popular and effective approach for implicit recommendat…

cs.LG2019119 cited

Hierarchical Graph Pooling with Structure Learning

Zhen Zhang, Jiajun Bu, Martin Ester +4

Graph Neural Networks (GNNs), which generalize deep neural networks to graph-structured data, have drawn considerable attention and achieved state-of-the-art performance in numerou…

cs.LG20194 cited

Online Knowledge Distillation with Diverse Peers

Defang Chen, Jian-Ping Mei, Can Wang +2

Distillation is an effective knowledge-transfer technique that uses predicted distributions of a powerful teacher model as soft targets to train a less-parameterized student model.…

cs.SI201924 cited

HAHE: Hierarchical Attentive Heterogeneous Information Network Embedding

Sheng Zhou, Jiajun Bu, Xin Wang +2

Heterogeneous information network (HIN) embedding has recently attracted much attention due to its effectiveness in dealing with the complex heterogeneous data. Meta path, which co…

cs.IR20146 cited

Attributes Coupling based Item Enhanced Matrix Factorization Technique for Recommender Systems

Yonghong Yu, Can Wang, Yang Gao

Recommender system has attracted lots of attentions since it helps users alleviate the information overload problem. Matrix factorization technique is one of the most widely employ…