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20232026
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cs.LG2026

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…

cs.LG2025

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…

cs.LG2024

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…

cs.LG2023

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…

cs.LG2023

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…