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cs.IR2024
Debiased Recommendation with Noisy Feedback
Haoxuan Li, Chunyuan Zheng, Wenjie Wang +3
Ratings of a user to most items in recommender systems are usually missing not at random (MNAR), largely because users are free to choose which items to rate. To achieve unbiased l…
cs.IR2023
A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems
Xu Huang, Jianxun Lian, Hao Wang +2
Recommendation systems effectively guide users in locating their desired information within extensive content repositories. Generally, a recommendation model is optimized to enhanc…