214 citations · 624 across the 11 of their papers we have counts for
14 papers · 1 filter
Transferable Fairness for Cold-Start Recommendation
Yunqi Li, Dingxian Wang, Hanxiong Chen +1
With the increasing use and impact of recommender systems in our daily lives, how to achieve fairness in recommendation has become an important problem. Previous works on fairness-…
Causal Inference for Recommendation: Foundations, Methods and Applications
Shuyuan Xu, Jianchao Ji, Yunqi Li +3
Recommender systems are important and powerful tools for various personalized services. Traditionally, these systems use data mining and machine learning techniques to make recomme…
A Survey on Trustworthy Recommender Systems
Yingqiang Ge, Shuchang Liu, Zuohui Fu +6
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely deployed in almost every corner of the web and facilitate the human decision-making process. How…
Fairness in Recommendation: Foundations, Methods and Applications
Yunqi Li, Hanxiong Chen, Shuyuan Xu +4
As one of the most pervasive applications of machine learning, recommender systems are playing an important role on assisting human decision making. The satisfaction of users and t…
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning
Juntao Tan, Shijie Geng, Zuohui Fu +4
Structural data well exists in Web applications, such as social networks in social media, citation networks in academic websites, and threads data in online forums. Due to the comp…
Graph Collaborative Reasoning
Hanxiong Chen, Yunqi Li, Shaoyun Shi +3
Graphs can represent relational information among entities and graph structures are widely used in many intelligent tasks such as search, recommendation, and question answering. Ho…