High-dimensional pseudo-logistic regression and classification with applications to gene expression data. - Chunming Zhang; Haoda Fu; Yuan Jiang; Tao Yu (Comput. Stat. Data Anal., 2007)

Identifying risk factors associate with hypoglycemic events. - Ran Duan; Haoda Fu; Chenchen Yu (CICARE, 2014)

Learning from Label and Feature Heterogeneity. - Pei Yang 001; Jingrui He; Hongxia Yang; Haoda Fu (ICDM, 2014)

A multi-scale non-parametric and parametric hybrid multi-category recognition algorithm with probabilistic outputs. - Zhao Lu; Haoda Fu; Gangbing Song (J. Exp. Theor. Artif. Intell., 2015)

Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. - Pei Yang 001; Hongxia Yang; Haoda Fu; Dawei Zhou 003; Jieping Ye; Theodoros Lappas; Jingrui He (ACM Trans. Knowl. Discov. Data, 2016)

A unified approach for subgroup identification and individualized treatment recommendation with applications to randomized control trials and observational studies. - Haoda Fu; Jin Zhou (Model. Assist. Stat. Appl., 2017)

Boosting Algorithms for Estimating Optimal Individualized Treatment Rules. - Duzhe Wang; Haoda Fu; Po-Ling Loh (CoRR, 2020)

Near-optimal Individualized Treatment Recommendations. - Haomiao Meng; Ying-Qi Zhao; Haoda Fu; Xingye Qiao (J. Mach. Learn. Res., 2020)

Query-augmented Active Metric Learning. - Yujia Deng; Yubai Yuan; Haoda Fu; Annie Qu (CoRR, 2021)

High-Dimensional Cost-constrained Regression Via Nonconvex Optimization. - Guan Yu; Haoda Fu; Yufeng Liu (Technometrics, 2022)

Fast Approximation of the Shapley Values Based on Order-of-Addition Experimental Designs. - Liuqing Yang; Yongdao Zhou; Haoda Fu; Min-Qian Liu; Wei Zheng (CoRR, 2023)

Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls. - Mochuan Liu; Yuanjia Wang; Haoda Fu; Donglin Zeng (J. Mach. Learn. Res., 2024)

Efficient Human-in-the-Loop Active Learning: A Novel Framework for Data Labeling in AI Systems. - Yiran Huang; Jian-Feng Yang; Haoda Fu (CoRR, 2025)