19 citations · 42 across the 5 of their papers we have counts for
5 papers
ICPE: An Item Cluster-Wise Pareto-Efficient Framework for Recommendation Debiasing
Yule Wang, Xin Xin, Yue Ding +2
Recommender system based on historical user-item interactions is of vital importance for web-based services. However, the observed data used to train the recommender model suffers…
Self-Supervised Reinforcement Learning for Recommender Systems
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
In session-based or sequential recommendation, it is important to consider a number of factors like long-term user engagement, multiple types of user-item interactions such as clic…
Graph Highway Networks
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
Graph Convolution Networks (GCN) are widely used in learning graph representations due to their effectiveness and efficiency. However, they suffer from the notorious over-smoothing…
Generalized Embedding Machines for Recommender Systems
Enneng Yang, Xin Xin, Li Shen +1
Factorization machine (FM) is an effective model for feature-based recommendation which utilizes inner product to capture second-order feature interactions. However, one of the maj…
Relational Collaborative Filtering:Modeling Multiple Item Relations for Recommendation
Xin Xin, Xiangnan He, Yongfeng Zhang +2
Existing item-based collaborative filtering (ICF) methods leverage only the relation of collaborative similarity. Nevertheless, there exist multiple relations between items in real…