5 papers
Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection
Hung Vinh Tran, Tong Chen, Hechuan Wen +3
Content-based recommendation systems (CRSs) utilize content features to predict user-item interactions, serving as essential tools for helping users navigate information-rich web s…
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong +3
Although numerous complex algorithms for treatment effect estimation have been developed in recent years, their effectiveness remains limited when handling insufficiently labeled t…
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
Hechuan Wen, Tong Chen, Guanhua Ye +3
Causal effect estimation (CEE) provides a crucial tool for predicting the unobserved counterfactual outcome for an entity. As CEE relaxes the requirement for ``perfect'' counterfac…
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Hechuan Wen, Tong Chen, Li Kheng Chai +3
Due to the imbalanced nature of networked observational data, the causal effect predictions for some individuals can severely violate the positivity/overlap assumption, rendering u…
Variational Counterfactual Prediction under Runtime Domain Corruption
Hechuan Wen, Tong Chen, Li Kheng Chai +3
To date, various neural methods have been proposed for causal effect estimation based on observational data, where a default assumption is the same distribution and availability of…