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会议论文（计算机／数据科学）
Competing for Sharable Arms in Multi-Player Multi-Armed Bandits (with Renzhe Xu, Haotian Wang, Xingxuan Zhang and Peng Cui), ICML, 2023, CCF中国计算机学会A类
Heterogeneous Treatment Effect with Locally Undersampled Data (with Anpeng Wu, Kun Kuang, Ruoxuan Xiong and Fei Wu), ICML, 2023, CCF中国计算机学会A类
Measure the Predictive Heterogeneity (with Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang and Peng Cui). ICLR, 2023
Factual Observation Based Heterogeneity Learning for Counterfactual Prediction (with Hao Zou, Haotian Wang, Renzhe Xu, Jian Pei, Junjian Ye and Peng Chi). CLeaR (Conference on Causal Learning and Reasoning), 2023.
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation (with Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqin Zhu, Yuxuan Liu, Furui Liu, Zhihua Wang and Fei Wu), AAAI, 2023, CCF中国计算机学会A类
Product Ranking for Revenue Maximization with Multiple Purchases (with Renzhe Xu, Xingxuan Zhang, Yafeng Zhang, Xiaolong Chen and Peng Cui), NeurIPS, 2022, CCF中国计算机学会A类
Distributionally Robust Optimization with Data Geometry (with Jiashuo Liu, Jiayun Wu, Peng Cui), NeurIPS, 2022, CCF中国计算机学会A类
Instrumental Variable Regression with Confounder Balancing (with Anpeng Wu, Kun Kuang and Fei Wu), ICML, 2022, CCF中国计算机学会A类
Counterfactual Prediction for Outcome-Oriented Treatments (with Hao Zou, Peng Cui, Jiangang Han, Shuiping Chen and Xuetao Ding), ICML, 2022, CCF中国计算机学会A类
Regulatory Instruments for Fair Personalized Pricing (with Renzhe Xu, Xingxuan Zhang, Peng Cui, Zheyan Shen and Jiazheng Xu), WWW, 2022, CCF中国计算机学会A类
Kernelized Heterogeneous Risk Minimization (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), NeurIPS, 2021, CCF中国计算机学会A类
Heterogeneous Risk Minimization (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), ICML, (Spotlight) 2021, CCF中国计算机学会A类
Invariant Adversarial Learning for Distributional Robustness (with Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang and Yishi Lin), AAAI, 2021, CCF中国计算机学会A类
Counterfactual Prediction for Bundle Treatment (with Hao Zou, Peng Cui, Zheyan Shen, Jianxin Ma, Hongxia Yang and Yue He), NeurIPS, 2020, CCF中国计算机学会A类
Algorithmic Decision Making with Conditional Fairness (with Renzhe Xu, Peng Cui, Kun Kuang, Lingjun Zhou, Zheyan Shen and Wei Cui), KDD , 2020, CCF中国计算机学会A类
Stable Learning via Differentiated Variable Decorrelation (with Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang and Zhitang Chen), KDD, 2020, CCF中国计算机学会A类
Stable Prediction with Model Misspecification and Agnostic Distribution Shift (with Kun Kuang, Ruoxuan Xiong, Peng Cui and Susan Athey), AAAI , 2020, CCF中国计算机学会A类
Causally Regularized Learning On Data with Agnostic Bias (with Zheyan Shen, Peng Cui and Kun Kuang), ACM MM (oral presentation), 2018, CCF中国计算机学会A类
Stable Prediction across Unknown Environments (with Kun Kuang, Peng Cui, Susan Athey and Ruoxuan Xiong), KDD (long presentation), 2018, CCF中国计算机学会A类
Estimating Causal Effects in the Wild via Differentiated Confounder Balancing (with Kun Kuang, Peng Cui, Meng Jiang and Shiqiang Yang), KDD (oral presentation), 2017, CCF中国计算机学会A类
Treatment Effect Estimation with Data-Driven Variable Decomposition (with Kun Kuang, Peng Cui, Meng Jiang, Shiqiang Yang and Fei Wang), AAAI, 2017, CCF中国计算机学会A类
How Out-of-Pocket Ratio Influences Readmission: An Analysis Based on Front Sheet of Inpatient Medical Record (with Luo He, Xiaolei Xie and Hongyan Liu), ICSH 2017, LNCS 10347, pp.67-78, 2017
期刊论文（英文, SCI/SSCI）
Distributionally Robust Optimization with Stable Adversarial Training (with Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou and Kun Kuang), IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear
Stable Prediction with Leveraging Seed Variable (with Kun Kuang, Haotian Wang, Yue Liu, Ruoxuan Xiong, Weiming Lu, Runze Wu, Yueting Zhuang, Fei Wu and Peng Cui), IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear
Differentiated Matching for Individual and Average Treatment Effect Estimation, (with Ziyu Zhao, Kun Kuang, Peng Cui, Runze Wu, Jun Xiao and Fei Wu), Data Mining and Knowledge Discovery , to appear
Learning Decomposed Representations for Treatment Effect Estimation (with Anpeng Wu, Junkun Yuan, Kun Kuang, Runze Wu, Qiang Zhu, Yueting Zhuang and Fei Wu), IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition (with Junkun Yuan, Anpeng Wu, Kun Kuang, Runze Wu, Fei Wu and Lanfen Lin), ACM Transactions on Knowledge Discovery from Data (TKDD) , 2022
Continuous Treatment Effect Estimation via Generated Adversarial de-Confounding, (with Kun Kuang, Yunzhe Li, Peng Cui, Hongxia Yang, Jianrong Tao and Fei Wu), Data Mining and Knowledge Discovery , 2021
Data-driven Variable Decomposition for Treatment Effect Estimation (with Kun Kuang, Peng Cui, Hao Zou, Jianrong Tao, Fei Wu and Shiqiang Yang), IEEE Transactions on Knowledge and Data Engineering (TKDE) , to appear (A shorter version appeared on AAAI2017)
Cross-Estimation for Decision Selection (with Xinyue Gu), Applied Stochastic Models in Business and Industry, 2020
Treatment Effect Estimation via Differentiated Confounder Balancing and Regression (with Kun Kuang, Peng Cui, Meng Jiang and Shiqiang Yang), ACM Transactions on Knowledge Discovery from Data (TKDD) , (A shorter version appeared on KDD2017), Vol.14, No.1, 6:1-6:25, 2020
On Estimation of Partially Linear Varying-Coefficient Transformation Models with Censored Data (with Baosheng Liang, Xingwei Tong and Jianguo Sun), Statistica Sinica, 22, 1963-1975, 2019
A Discrete Spatial Model for Wafer Yield Prediction (with Hao Wang, Seung Hoon Tong, In Kap Chang and Kaibo Wang), Quality Engineering, Vol.30, Issue 2, 169-182, 2018
Hierarchical Models for the Spatial-Temporal Carbon Nanotube Height Variations (with Jialing Tao, Kaibo Wang, Liang Liu and Qi Cai), International Journal of Production Research, Vol. 54, No. 21, 6613-6632, 2016
A Spatial Variable Selection Method for Monitoring Product Surface (with Kaibo Wang and Wei Jiang), International Journal of Production Research, Vol. 54, No. 14, 4161-4181, 2016
Counterfactual Decomposition of Movie Star Effects with Star Selection (with Angela Liu and Tridib Mazumdar), Management Science, Vol.61, No.7, pp.1704-1721, 2015
Simultaneous Monitoring of Process Mean Vector and Covariance Matrix via Penalized Likelihood Estimation (with Kaibo Wang and Arthur Yeh), Computational Statistics and Data Analysis, 78, 206-217, 2014
Trends in China's Gender Employment and Pay Gap: Estimating Gender Pay Gaps with Employment Selection (with Wei Chi), Journal of Comparative Economics, 42, 708-725, 2014
Monitoring Covariance Matrix via Penalized Likelihood Estimation (with Kaibo Wang and Arthur Yeh), IIE Transactions, 45, 132-146, 2013
Monitoring Multivariate Process Variability with Individual Observations via Penalized Likelihood Estimation (with Arthur Yeh and Kaibo Wang), International Journal of Production Research, Vol. 50, No. 22, 6624-6638, 2012
Forward Adaptive Banding for Estimating Large Covariance Matrices (with Chenlei Leng), Biometrika, 94, 4, pp.821-830, 2011 (统计学四大顶尖期刊之一)
Decomposition of the increase in earnings inequality in urban China: A distributional approach (with Wei Chi and Qiumei Yu), China Economic Review, 22, 299-312, 2011
Least Squares Approximations With a Diverging Number of Parameters (with Chenlei Leng), Statistics and Probability Letters, 80, 254-261, 2010
Asymptotically Distribution-Free Goodness-of-Fit Testing: A Unifying View, Econometric Reviews, 28(6):632-657, 2009
Shrinkage tuning parameter selection with a diverging number of parameters (with Hansheng Wang and Chenlei Leng), Journal of the Royal Statistical Society, Series B (Statistical Methodology), 71, Part 3, pp. 671-683, 2009 (统计学四大顶尖期刊之一)
Glass ceiling or sticky floor? Examining the gender earnings differential across the earnings distribution in urban China, 1987–2004 (with Wei Chi), Journal of Comparative Economics, 36, 243-263, 2008 (此论文获得首届麦肯锡中国经济学奖)
Nonparametric Testing of An Exclusion Restriction in Quantile Regression, Communications in Statistics—Theory and Methods, 37: 2877-2889, 2008
Regularization in statistics (with discussion and rejoinder, with Peter Bickel), Test, Vol. 15, No. 2, pp. 271-344, 2006
文集章节（英文）
Curse of Dimensionality Revisited: Collapse of the Particle Filter in Very Large Scale Systems (with Thomas Bengtsson and Peter Bickel), IMS Collections, Probability and Statistics: Essays in Honor of David A. Freedman, Vol. 2, 316-334, 2008
Sharp Failure Rates for the Bootstrap Particle Filter in High Dimensions (with Peter Bickel and Thomas Bengtsson), IMS Collections, Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh, Vol. 3, 318-329, 2008
Local Polynomial Regression on Unknown Manifolds (with Peter Bickel), IMS Lecture Notes–Monograph Series, Complex Datasets and Inverse Problems: Tomography, Networks and Beyond, Vol.54, 177-186, Vol. 54, 177-186, 2007
期刊论文（中文）
高管个人特征与公司业绩——基于机器学习的经验证据（与陆瑶，张叶青，赵浩宇），管理科学学报，即将发表
新浪企业微博口碑传播的实证研究（与张晶，黄京华，严威合作），清华大学学报（自然科学版）, 54卷，第5期，649-654，2014
ERP实施对企业绩效影响的实证研究——基于倾向性得分匹配法 （与张露，黄京华合作），清华大学学报（自然科学版）, 53卷，第1期，2013
人力资本对我国区域创新及经济增长的影响_基于空间计量的实证研究 （与钱晓烨，迟巍合作），数量经济技术经济研究， 107-121，第4期， 2010
基于收入分布的收入差距扩大成因的分解（与迟巍，余秋梅合作），数量经济技术经济研究，52-64，第9期，2008
一种新的收入差距研究的计量方法_基于分布函数的半参数化估计（与迟巍，余秋梅合作），数量经济技术经济研究，119-129，第8期， 2007
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