44 citations · 101 across the 9 of their papers we have counts for
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cs.IR2022★ 26 cited
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…
cs.IR2022
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…
cs.LG2022★ 1 cited
Deep Causal Reasoning for Recommendations
Yaochen Zhu, Jing Yi, Jiayi Xie +1
Traditional recommender systems aim to estimate a user's rating to an item based on observed ratings from the population. As with all observational studies, hidden confounders, whi…