谷歌学术主页
https://scholar.google.com/citations?hl=zh-CN&user=GaJXFWMAAAAJ
1. Qianyi Chen, Anpeng Wu, Bo Li, Lu Deng, Yong Wang. (2026). Journal to the Center of the Cluster: Harnessing Interior Nodes for A/B Testing under Network Interference. ICLR 2026.
2. Kang Wang, Renzhe Xu, Bo Li. (2026). Lower Bias, Higher Welfare: How Creator Competition Reshapes Bias-Variance Tradeoff in Recommendation Platforms? KDD 2026.
3. Bowen Shi, Xiaojie Mao, Mochen Yang, Bo Li. (2025). What, Why, and How: An Empiricist’s Guide to Double/Debiased Machine Learning. Information Systems Research, forthcoming.
4. Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui. (2025). Ppa-game: Characterizing and learning competitive dynamics among online content creators. KDD 2025.
5. Renzhe Xu, Kang Wang, Bo Li. (2025). Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. ICML 2025.
6. Anshuman Chhabra, Bo Li, Jian Chen, Prasant Mohapatra, Hongfu Liu. (2025). Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models. ICML 2025 (Oral).
7. Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Fei Wu, Kun Kuang. (2025). Learning double balancing representation for heterogeneous dose-response curve estimation. Neural Networks, 107600.
8. Ziyu Zhao, Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Zhihua Wang, Fei Wu. (2025). Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(2), 823–836.
9. Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui. (2024). Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications. ICML 2024.
10. Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu. (2024). Contrastive balancing representation learning for heterogeneous dose-response curves estimation. AAAI 2024.
11. Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui. (2024). Enhancing Distributional Stability among Sub-populations. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTAT) 2024.
12. Ziyu Zhao, Kun Kuang, Bo Li, Peng Cui, Runze Wu, Jun Xiao, Fei Wu. (2023). Differentiated matching for individual and average treatment effect estimation. Data Mining and Knowledge Discovery, 37(1), 205–227.
13. Kun Kuang, Haotian Wang, Yue Liu, Ruoxuan Xiong, Runze Wu, Weiming Lu, Yueting Zhuang, Fei Wu, Peng Cui, Bo Li. (2023). Stable prediction with leveraging seed variable. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(6), 6392–6404.
14. Anpeng Wu, Junkun Yuan, Kun Kuang, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu. (2023). Learning decomposed representations for treatment effect estimation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(5), 4989–5001.
15. Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li. (2023). Distributionally robust learning with stable adversarial training. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(11), 11288–11300.
16. Qianyi Chen, Bo Li, Lu Deng, Yong Wang. (2023). Optimized covariance design for ab test on social network under interference. NeurIPS 2023.
17. Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu. (2023). Stable estimation of heterogeneous treatment effects. ICML 2023.
18. Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui. (2023). Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. ICML 2023.
19. Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqin Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu. (2023). Learning instrumental variable from data fusion for treatment effect estimation. AAAI 2023.
20. Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui. (2023). Measure the predictive heterogeneity. ICLR 2023.
21. Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Yejun Jian, Peng Cui. (2023). Factual observation based heterogeneity learning for counterfactual prediction. Conference on Causal Learning and Reasoning 2023.
22. Kun Kuang, Peng Cui, Hao Zou, Bo Li, Jianrong Tao, Fei Wu, Shiqiang Yang. (2022). Data-driven Variable Decomposition for Treatment Effect Estimation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(5), 2120–2134.
23. Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin. (2022). Auto IV: Counterfactual prediction via automatic instrumental variable decomposition. ACM Transactions on Knowledge Discovery from Data (TKDD), 16(4), 1–20.
24. Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui. (2022). Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS 2022.
25. Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui. (2022). Distributionally Robust Optimization with Data Geometry. NeurIPS 2022.
26. Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding, Peng Cui. (2022). Counterfactual prediction for outcome-oriented treatments. ICML 2022.
27. Anpeng Wu, Kun Kuang, Bo Li, Fei Wu. (2022). Instrumental variable regression with confounder balancing. ICML 2022.
28. Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui. (2022). Regulatory instruments for fair personalized pricing. WWW 2022.
29. Kun Kuang, Yunzhe Li, Bo Li, Peng Cui, Hongxia Yang, Jianrong Tao, Fei Wu. (2021). Continuous treatment effect estimation via generative adversarial de-confounding. Data Mining and Knowledge Discovery, 35(6), 2467–2497.
30. Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen. (2021). Kernelized Heterogeneous Risk Minimization. NeurIPS 2021.
31. Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen. (2021). Heterogeneous risk minimization. ICML 2021 (Spotlight).
32. Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin. (2021). Stable adversarial learning under distributional shifts. AAAI 2021.
33. Xinyue Gu, Bo Li. (2020). Cross-estimation for decision selection. Applied Stochastic Models in Business and Industry, 36(5), 932–958.
34. Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He. (2020). Counterfactual Prediction for Bundle Treatment. NeurIPS 2020.
35. Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui. (2020). Algorithmic decision making with conditional fairness. KDD 2020.
36. Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen. (2020). Stable learning via differentiated variable decorrelation. KDD 2020.
37. Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li. (2020). Stable prediction with model misspecification and agnostic distribution shift. AAAI 2020.
38. Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Yashen Wang, Fei Wu, Shiqiang Yang. (2019). Treatment effect estimation via differentiated confounder balancing and regression. ACM Transactions on Knowledge Discovery from Data (TKDD), 14(1), 1–25.
39. Bo Li, Baosheng Liang, Xingwei Tong, Jianguo Sun. (2019). On estimation of partially linear varying-coefficient transformation models with censored data. Statistica Sinica, 29(4), 1963–1975.
40. Hao Wang, Bo Li, Seung Hoon Tong, In-Kap Chang, Kaibo Wang. (2018). A discrete spatial model for wafer yield prediction. Quality Engineering, 30(2), 169–182.
41. Kun Kuang, Peng Cui, Susan Athey, Ruoxuan Xiong, Bo Li. (2018). Stable prediction across unknown environments. KDD 2018.
42. Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, Peixuan Chen. (2018). Causally regularized learning with agnostic data selection bias. ACM MM 2018.
43. Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang. (2017). Estimating treatment effect in the wild via differentiated confounder balancing. KDD 2017.
44. Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, Fei Wang. (2017). Treatment effect estimation with data-driven variable decomposition. AAAI 2017.
45. Luo He, Xiaolei Xie, Hongyan Liu, Bo Li. (2017). How out-of-pocket ratio influences readmission: An analysis based on front sheet of inpatient medical record. International Conference on Smart Health, 67–78.
46. Kaibo Wang, Wei Jiang, Bo Li. (2016). A spatial variable selection method for monitoring product surface. International Journal of Production Research, 54(14), 4161–4181.
47. Jialing Tao, Kaibo Wang, Bo Li, Liang Liu, Qi Cai. (2016). Hierarchical models for the spatial-temporal carbon nanotube height variations. International Journal of Production Research, 54(21), 6613–6632.
48. Angela Liu, Tridib Mazumdar, Bo Li. (2015). Counterfactual decomposition of movie star effects with star selection. Management Science, 61(7), 1704–1721.
49. Bo Li, Chi Wang, Li Wei, Bo Li. (2014). Trends in China’s gender employment and pay gap: Estimating gender pay gaps with employment selection. Journal of Comparative Economics, 42(3), 708–725.
50. Kaibo Wang, Arthur B. Yeh, Bo Li. (2014). Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation. Computational Statistics & Data Analysis, 78, 206–217.
51. Bo Li, Kaibo Wang, Arthur B. Yeh. (2013). Monitoring the covariance matrix via penalized likelihood estimation. IIE Transactions, 45(2), 132–146.
52. Arthur B. Yeh, Bo Li, Kaibo Wang. (2012). Monitoring multivariate process variability with individual observations via penalised likelihood estimation. International Journal of Production Research, 50(22), 6624–6638.
53. Wei Chi, Bo Li, Qiumei Yu. (2011). Decomposition of the increase in earnings inequality in urban China: A distributional approach. China Economic Review, 22(3), 299–312.
54. Chenlei Leng, Bo Li. (2011). Forward adaptive banding for estimating large covariance matrices. Biometrika, 98(4), 821–830.
55. Chenlei Leng, Bo Li. (2010). Least squares approximation with a diverging number of parameters. Statistics & Probability Letters, 80(3–4), 254–261.
56. Bo Li. (2009). Asymptotically distribution-free goodness-of-fit testing: A unifying view. Econometric Reviews, 28(6), 632–657.
57. Hansheng Wang, Bo Li, Chenlei Leng. (2009). Shrinkage tuning parameter selection with a diverging number of parameters. Journal of the Royal Statistical Society Series B: Statistical Methodology, 71(3), 671–683.
58. Wei Chi, Bo Li. (2008). Glass ceiling or sticky floor? Examining the gender earnings differential across the earnings distribution in urban China, 1987–2004. Journal of Comparative Economics, 36(2), 243–263.
59. Bo Li. (2008). Nonparametric testing of an exclusion restriction in quantile regression. Communications in Statistics—Theory and Methods, 37(18), 2877–2889.
60. Peter Bickel, Bo Li, Thomas Bengtsson. (2008). Sharp failure rates for the bootstrap particle filter in high dimensions. In Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh (Vol. 3, pp. 318–330). Institute of Mathematical Statistics Collections.
61. Thomas Bengtsson, Peter Bickel, Bo Li. (2008). Curse-of-dimensionality revisited: Collapse of the particle filter in very large scale systems. In Probability and Statistics: Essays in Honor of David A. Freedman (Vol. 2, pp. 316–335). Institute of Mathematical Statistics Collections.
62. Peter J. Bickel, Bo Li. (2007). Local polynomial regression on unknown manifolds. Institute of Mathematical Statistics Lecture Notes–Monograph Series, 177–186.
63. Peter J. Bickel, Bo Li. (2006). Regularization in statistics (with discussion and rejoinder). Test, 15(2), 303–344.
64. 陆瑶，张叶青，黎波，赵浩宇. (2021). 高管个人特征与公司业绩 —— 基于机器学习的经验证据. 管理科学学报, 23(2), 120-140.
65. 张晶，黄京华，黎波，严威. (2014). 新浪企业微博口碑传播的实证研究. 清华大学学报：自然科学版, 54(5), 649-654.
66. 张露，黄京华，黎波. (2013). ERP 实施对企业绩效影响的实证研究 —— 基于倾向得分匹配法. 清华大学学报：自然科学版, (1), 117-121.
67. 钱晓烨，迟巍，黎波. (2010). 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. 数量经济技术经济研究, (4), 107-121.
68. 迟巍，黎波，余秋梅. (2008). 基于收入分布的收入差距扩大成因的分解. 数量经济技术经济研究, 25(9), 52-64.
69. 黎波，迟巍，余秋梅. (2007). 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. 数量经济技术经济研究, 24(8), 119-129.
