5 papers
SkillTFM: Gated Skill Evolution for Training-Free Adaptation of Tabular Foundation Models
Yi He, Zhengkang Guan, Anpeng Wu +3
Tabular data are ubiquitous in real-world applications and are crucial for data-driven prediction and decision-making across science, industry, finance, healthcare, and public serv…
Causal Discovery for Irregularly Time Series with Consistency Guarantees
Weihong Li, Baohong Li, Anpeng Wu +4
This paper studies causal discovery in irregularly sampled time series-a key challenge in risk-sensitive domains like finance, healthcare, and climate science, where missing data a…
Sequential Treatment Effect Estimation with Unmeasured Confounders
Yingrong Wang, Anpeng Wu, Baohong Li +4
This paper studies the cumulative causal effects of sequential treatments in the presence of unmeasured confounders. It is a critical issue in sequential decision-making scenarios…
General Information Metrics for Improving AI Model Training Efficiency
Jianfeng Xu, Congcong Liu, Xiaoying Tan +8
To address the growing size of AI model training data and the lack of a universal data selection methodology-factors that significantly drive up training costs -- this paper presen…
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
Anpeng Wu, Kun Kuang, Ruoxuan Xiong +4
In causal inference, encouragement designs (EDs) are widely used to analyze causal effects, when randomized controlled trials (RCTs) are impractical or compliance to treatment cann…