414 citations · 1.1k across the 4 of their papers we have counts for
4 papers
A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation
Le Wu, Xiangnan He, Xiang Wang +2
Influenced by the great success of deep learning in computer vision and language understanding, research in recommendation has shifted to inventing new recommender models based on…
Bias and Debias in Recommender System: A Survey and Future Directions
Jiawei Chen, Hande Dong, Xiang Wang +3
While recent years have witnessed a rapid growth of research papers on recommender system (RS), most of the papers focus on inventing machine learning models to better fit user beh…
How to Retrain Recommender System? A Sequential Meta-Learning Method
Yang Zhang, Fuli Feng, Chenxu Wang +4
Practical recommender systems need be periodically retrained to refresh the model with new interaction data. To pursue high model fidelity, it is usually desirable to retrain the m…
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He, Kuan Deng, Xiang Wang +3
Graph Convolution Network (GCN) has become new state-of-the-art for collaborative filtering. Nevertheless, the reasons of its effectiveness for recommendation are not well understo…