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Publications and Preprints

[Machine Learning and Economics] 

[Statistical Inference in Dynamical Systems] 

[High-Dimensional Nonparametric Statistics] 

[Brain Imaging Analysis and Biomedical Research]

Preprints 

(Note:     students under my supervision;  * corresponding author)

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  • An ODE model for dynamic matching in heterogeneous networks. [pdf][code]

Xiaowu Dai* and Hengzhi He.

Preprint, 2023+.

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  • Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions. [pdf][code]

Jiale Han and Xiaowu Dai*. 

Preprint, 2023+.

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  • Double matching under complementary preferences. [pdf][code]

Yuantong Li, Guang Cheng, and Xiaowu Dai*.

Preprint, 2023+.

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  • Incentive-aware recommender systems in two-sided markets. [pdf]

Xiaowu Dai, Yuan Qi, and Michael Jordan.  

Preprint, 2022+.

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  • Post-regularization confidence bands for ordinary differential equations. [pdf]

Xiaowu Dai and Lexin Li. 

Preprint, 2022+; Under Revisions at Journal of Machine Learning Research.

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  • Nonparametric estimation via mixed gradients. [pdf]

Xiaowu Dai.

Preprint, 2022+; Under Revisions at Journal of the Royal Statistical Society: Series B.

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  • A resampling approach for causal inference on novel two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease. [pdf]

Xiaowu Dai, Saad Mouti, Marjorie Lima do Vale, Sumantra Ray, Jeffrey Bohn, and Lisa Goldberg.​ 

Preprint, 2022+; Under Revisions at Statistics in Biosciences.

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  • Another look at statistical calibration: A non-asymptotic theory and prediction-oriented optimality. [pdf]

Xiaowu Dai and Peter Chien.​ 

Preprint, 2022+.

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  • Selection and estimation optimality in high dimensions with the TWIN penalty. [pdf]

Xiaowu Dai and Jared Huling.

Preprint, 2022+.​

Publications​

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Xiaowu Dai, Xiang Lyu, and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2022.

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  • Orthogonalized kernel debiased machine learning for multimodal data analysis. [journal][preprint]

Xiaowu Dai and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2021.

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  • Learning strategies in decentralized matching markets under uncertain preferences. [journal][preprint]

Xiaowu Dai and Michael Jordan.​

Journal of Machine Learning Research (JMLR), 2021.

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Xiaowu Dai and Michael Jordan.​

Advances in Neural Information Processing Systems (NeurIPS), 2021.

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Xiaowu Dai and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2021.

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  • A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: A framework to guide further research and approaches to evidence-based practice. [journal][pubmed]

Marjorie Lima do Vale, Luke Buckner, Claudia-Gabriela Mitrofan, Kai Sento Kargbo, Rajna Golubic, Ali Ahsan Khalid, Sammyia Ashraf, Saad Mouti, Xiaowu Dai, David Unwin, Jeffrey Bohn, Lisa Goldberg, and Sumantra Ray.​ 

Nutrition Research Reviews (NRR), 2021.

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Xiaowu Dai and Yuhua Zhu.

Journal of Statistical Theory and Practice (JSTP), special issue on "Advances in Deep Learning", 2020. 

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  • High-dimensional smoothing splines and application in Alzheimer's disease prediction using magnetic resonance imaging. [journal][preprint]

Xiaowu Dai.

Statistics in Biopharmaceutical Research (SBR), 2019.

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  • High-dimensional varying coefficient models for Alzheimer's disease diagnosis with longitudinal and heterogeneous structural MR images. [journal]

Xiaowu Dai.

Alzheimer's & Dementia (AD), 2018.

Miscellaneous​

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  • Statistical learning-aided design for a blockchain payment system. [pdf]

Xiaowu Dai. 

Research Vignette, Simons Institute for the Theory of Computing, 2020.

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  • Statistical machine learning for complex data sets. [pdf]

Xiaowu Dai. 

Ph.D. Thesis, Department of Statistics, UW-Madison, 2019.

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