Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications (with Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou and Peng Cui), ICML 2024
Enhancing Distributional Stability among Subpopulations (with Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng and Peng Cui), AISTAT 2024
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation (with Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Xiaoqing Yang, Xuan Qin, Jiecheng Guo, Few Wu and Kun Kuang), AAAI 2024
Optimized Covariance Design for AB Test on Social Network Under Interference (with Qianyi Chen, Lu Deng and Yong Wang), NeurIPS, 2023
Competing for Sharable Arms in Multi-Player Multi-Armed Bandits (with Renzhe Xu, Haotian Wang, Xingxuan Zhang and Peng Cui), ICML, 2023
Stable Estimation of Heterogeneous Treatment Effects (with Anpeng Wu, Kun Kuang, Ruoxuan Xiong and Fei Wu), ICML, 2023
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, 2023Product Ranking for Revenue Maximization with Multiple Purchases (with Renzhe Xu, Xingxuan Zhang, Yafeng Zhang, Xiaolong Chen and Peng Cui), NeurIPS, 2022
Distributionally Robust Optimization with Data Geometry (with Jiashuo Liu, Jiayun Wu, Peng Cui), NeurIPS, 2022
Instrumental Variable Regression with Confounder Balancing (with Anpeng Wu, Kun Kuang and Fei Wu), ICML, 2022
Counterfactual Prediction for Outcome-Oriented Treatments (with Hao Zou, Peng Cui, Jiangang Han, Shuiping Chen and Xuetao Ding), ICML, 2022
Regulatory Instruments for Fair Personalized Pricing (with Renzhe Xu, Xingxuan Zhang, Peng Cui, Zheyan Shen and Jiazheng Xu), WWW, 2022
Kernelized Heterogeneous Risk Minimization (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), NeurIPS, 2021
Heterogeneous Risk Minimization (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), ICML, (Spotlight) 2021
Invariant Adversarial Learning for Distributional Robustness (with Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang and Yishi Lin), AAAI, 2021
Counterfactual Prediction for Bundle Treatment (with Hao Zou, Peng Cui, Zheyan Shen, Jianxin Ma, Hongxia Yang and Yue He), NeurIPS, 2020
Algorithmic Decision Making with Conditional Fairness (with Renzhe Xu, Peng Cui, Kun Kuang, Lingjun Zhou, Zheyan Shen and Wei Cui), KDD , 2020
Stable Learning via Differentiated Variable Decorrelation (with Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang and Zhitang Chen), KDD, 2020
Stable Prediction with Model Misspecification and Agnostic Distribution Shift (with Kun Kuang, Ruoxuan Xiong, Peng Cui and Susan Athey), AAAI , 2020
Causally Regularized Learning On Data with Agnostic Bias (with Zheyan Shen, Peng Cui and Kun Kuang), ACM Multimedia(oral presentation), 2018
Stable Prediction across Unknown Environments (with Kun Kuang, Peng Cui, Susan Athey and Ruoxuan Xiong), ACM KDD (long presentation), 2018
Estimating Causal Effects in the Wild via Differentiated Confounder Balancing (with Kun Kuang, Peng Cui, Meng Jiang and Shiqiang Yang), ACM KDD (oral presentation), 2017
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
Treatment Effect Estimation with Data-Driven Variable Decomposition (with Kun Kuang, Peng Cui, Meng Jiang, Shiqiang Yang and Fei Wang), AAAI, 2017
Networked Instrumental Variable for Treatment Effect Estimation with Unobserved Confounders (with Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Fei Wu and Kun Kuang), IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear
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 , to appear
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, to appear
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, 2019
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, 2012
Forward Adaptive Banding for Estimating Large Covariance Matrices (with Chenlei Leng), Biometrika, 94, 4, pp.821-830, 2011
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, 71, Part 3, pp. 671-683, 2009
Nonparametric Testing of An Exclusion Restriction in Quantile Regression, Communications in Statistics— Theory and Methods, 37: 2877-2889, 2008
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
Regularization in statistics (with discussion and rejoinder, with Peter Bickel), Test, Vol. 15, No. 2, pp. 271-344, 2006
