26 citations · 45 across the 5 of their papers we have counts for
5 papers · 1 filter
Path-Specific Counterfactual Fairness for Recommender Systems
Yaochen Zhu, Jing Ma, Liang Wu +3
Recommender systems (RSs) have become an indispensable part of online platforms. With the growing concerns of algorithmic fairness, RSs are not only expected to deliver high-qualit…
Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and Generalization
Yaochen Zhu, Jing Ma, Jundong Li
In the era of information overload, recommender systems (RSs) have become an indispensable part of online service platforms. Traditional RSs estimate user interests and predict the…
Mutually-Regularized Dual Collaborative Variational Auto-encoder for Recommendation Systems
Yaochen Zhu, Zhenzhong Chen
Recently, user-oriented auto-encoders (UAEs) have been widely used in recommender systems to learn semantic representations of users based on their historical ratings. However, sin…
Deep Deconfounded Content-based Tag Recommendation for UGC with Causal Intervention
Yaochen Zhu, Xubin Ren, Jing Yi +1
Traditional content-based tag recommender systems directly learn the association between user-generated content (UGC) and tags based on collected UGC-tag pairs. However, since a UG…
Variational Bandwidth Auto-encoder for Hybrid Recommender Systems
Yaochen Zhu, Zhenzhong Chen
Hybrid recommendations have recently attracted a lot of attention where user features are utilized as auxiliary information to address the sparsity problem caused by insufficient u…