Publications​
(Note: students under my supervision; * corresponding author)
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2024
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Nonparametric estimation via partial derivatives. [journal][preprint][UCLA StatsDS News][UCLA Physical Sciences News]
Xiaowu Dai*.
Journal of the Royal Statistical Society Series B: Statistical Methodology (JRSSB), 2024. [lead article]​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​
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Xiaowu Da​i* and Lexin Li.
Journal of Machine Learning Research (JMLR), 2024.
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Xiaowu Dai*, Wenlu Xu, Yuan Qi, and Michael Jordan.
ACM Transactions on Recommender Systems (TORS), 2024.
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Two-sided competing matching recommendation markets with quota and complementary preferences constraints. [proceedings][preprint][code]
Yuantong Li, Guang Cheng, and Xiaowu Dai*.
International Conference on Machine Learning (ICML), 2024.
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A data envelopment analysis approach for assessing fairness in resource allocation: Application to kidney exchange programs. [pdf][code]
Ali Kaazempur-Mofrad, and Xiaowu Dai*.
Preprint, 2024.
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Fairness-aware organ exchange and kidney paired donation. [pdf][code]
Mingrui Zhang, Xiaowu Dai, and Lexin Li.
Preprint, 2024.
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Conformal online auction design. [pdf][code][older version, code]
Jiale Han and Xiaowu Dai*.
Preprint, 2024.
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Dynamic online recommendation for two-sided market with Bayesian incentive compatibility. [pdf]
Yuantong Li, Guang Cheng, and Xiaowu Dai*.
Preprint, 2024.
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Multi-layer kernel machines: Fast and optimal nonparametric regression with uncertainty quantification. [pdf][code][PyPI]
Xiaowu Dai* and Huiying Zhong.
Preprint, 2024.
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2023
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Xiaowu Dai*, Xiang Lyu, and Lexin Li.
Journal of the American Statistical Association: Theory and Methods (JASA), 2023. [lead article]
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Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas. [journal][reprint][preprint][code]
Jiayi Li, Yuantong Li, and Xiaowu Dai*.​
Journal of the Royal Statistical Society Series B: Statistical Methodology (JRSSB), 2023.
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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. [journal][reprint][preprint][code]
Xiaowu Dai*, Saad Mouti, Marjorie Lima do Vale, Sumantra Ray, Jeffrey Bohn, and Lisa Goldberg.​
Statistics in Biosciences (SIBS), 2023.
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Selection and estimation optimality in high dimensions with the TWIN penalty. [pdf]
Xiaowu Dai and Jared Huling.​
Preprint, 2023.
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Xiaowu Dai* and Hengzhi He.
Preprint, 2023.
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2022​
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Orthogonalized kernel debiased machine learning for multimodal data analysis. [journal][reprint][preprint]
Xiaowu Dai and Lexin Li.
Journal of the American Statistical Association: Theory and Methods (JASA), 2022. [lead article]
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Xiaowu Dai and Lexin Li.​
Journal of the American Statistical Association: Theory and Methods (JASA), 2022. [lead article]
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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][reprint][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), 2022.
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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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pre-2022​
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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. [lead article]
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Learning in multi-stage decentralized matching markets. [proceedings][preprint]
Xiaowu Dai and Michael Jordan.​
Advances in Neural Information Processing Systems (NeurIPS), 2021.
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On large batch training and sharp minima: A Fokker-Planck perspective. [journal][reprint][preprint]​[older version]
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][reprint][preprint]
Xiaowu Dai.
Statistics in Biopharmaceutical Research (SBR), 2020.
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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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High-dimensional varying coefficient models for Alzheimer's disease diagnosis with longitudinal and heterogeneous structural MR images.
Xiaowu Dai.
Alzheimer's & Dementia (AD), 2018.