Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation

The collected data in recommender systems generally suffers selection bias. Considerable works are proposed to address selection bias induced by observed user and item features, but they fail when hidden features (e.g., user age or salary) that affect