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黎波

管理科學與工程系    長聘副教授

電話:(86)(10)62795143

辦公室:李華樓B421

郵箱:libo@sem.tsinghua.edu.cn

開放時間:郵件預約

教育經曆

2002年 北京大學 數學學士

2006年 加州大學伯克利分校 統計學博士

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工作經曆

2006 至今,先後擔任BETVLCTOR伟德官方网站 助理教授、副教授、長聘副教授,主持國家自然科學基金青年項目、面上項目,北京市青年英才計劃項目,BETVLCTOR伟德官方网站自主科研項目,及騰訊等公司合作項目。曾獲得第四屆BETVLCTOR伟德官方网站“清韻燭光”我最喜愛的教師稱号。


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講授課程

概率論與數理統計、高等數理統計、大數據分析

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研究領域

複雜數據驅動的決策與預測、人工智能與經濟社會

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學術成果

谷歌學術主頁

https://scholar.google.com/citations?hl=zh-CN&user=GaJXFWMAAAAJ


會議論文(計算機/數據科學)


  • 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, CCF中國計算機學會A類

  • Optimized Covariance Design for AB Test on Social Network Under Interference (with Qianyi Chen, Lu Deng and Yong Wang), NeurIPS, 2023, CCF中國計算機學會A類

  • Competing for Sharable Arms in Multi-Player Multi-Armed Bandits  (with Renzhe Xu, Haotian Wang, Xingxuan Zhang and Peng Cui), ICML, 2023, CCF中國計算機學會A類

  • Stable Estimation of Heterogeneous Treatment Effects (with Anpeng Wu, Kun Kuang, Ruoxuan Xiong and Fei Wu), ICML, 2023, CCF中國計算機學會A類

  • 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中國計算機學會A類

  • Product Ranking for Revenue Maximization with Multiple Purchases (with Renzhe Xu, Xingxuan Zhang, Yafeng Zhang, Xiaolong Chen and Peng Cui), NeurIPS, 2022, CCF中國計算機學會A類

  • Distributionally Robust Optimization with Data Geometry (with Jiashuo Liu, Jiayun Wu, Peng Cui), NeurIPS, 2022, CCF中國計算機學會A類

  • Instrumental Variable Regression with Confounder Balancing (with Anpeng Wu, Kun Kuang and Fei Wu), ICML, 2022, CCF中國計算機學會A類

  • Counterfactual Prediction for Outcome-Oriented Treatments  (with Hao Zou, Peng Cui, Jiangang Han, Shuiping Chen and Xuetao Ding), ICML, 2022, CCF中國計算機學會A類

  • Regulatory Instruments for Fair Personalized Pricing (with Renzhe Xu, Xingxuan Zhang, Peng Cui, Zheyan Shen and Jiazheng Xu), WWW, 2022, CCF中國計算機學會A類

  • Kernelized Heterogeneous Risk Minimization  (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), NeurIPS, 2021, CCF中國計算機學會A類

  • Heterogeneous Risk Minimization  (with Jiashuo Liu, Zheyuan Hu, Peng Cui and Zheyan Shen), ICML, (Spotlight) 2021, CCF中國計算機學會A類

  • Invariant Adversarial Learning for Distributional Robustness  (with Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang and Yishi Lin), AAAI, 2021, CCF中國計算機學會A類

  • Counterfactual Prediction for Bundle Treatment (with Hao Zou, Peng Cui, Zheyan Shen, Jianxin Ma, Hongxia Yang and Yue He), NeurIPS, 2020, CCF中國計算機學會A類

  • Algorithmic Decision Making with Conditional Fairness (with Renzhe Xu, Peng Cui, Kun Kuang, Lingjun Zhou, Zheyan Shen and Wei Cui), KDD , 2020, CCF中國計算機學會A類

  • Stable Learning via Differentiated Variable Decorrelation (with Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang and Zhitang Chen), KDD, 2020, CCF中國計算機學會A類

  • Stable Prediction with Model Misspecification and Agnostic Distribution Shift (with Kun Kuang, Ruoxuan Xiong, Peng Cui and Susan Athey), AAAI , 2020, CCF中國計算機學會A類

  • Causally Regularized Learning On Data with Agnostic Bias (with Zheyan Shen, Peng Cui and Kun Kuang), ACM MM (oral presentation), 2018, CCF中國計算機學會A類

  • Stable Prediction across Unknown Environments (with Kun Kuang, Peng Cui, Susan Athey and Ruoxuan Xiong), KDD (long presentation), 2018, CCF中國計算機學會A類

  • 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中國計算機學會A類

  • Treatment Effect Estimation with Data-Driven Variable Decomposition (with Kun Kuang, Peng Cui, Meng Jiang, Shiqiang Yang and Fei Wang), AAAI,  2017, CCF中國計算機學會A類

  • 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


期刊論文(英文, SCI/SSCI)

  • 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 , 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 (統計學四大頂尖期刊之一)

  • 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 (統計學四大頂尖期刊之一)

  • 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 (此論文獲得首屆麥肯錫中國經濟學獎)

  • 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


文集章節(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


期刊論文(中文)

  • 高管個人特征與公司業績——基于機器學習的經驗證據(與陸瑤,張葉青,趙浩宇),管理科學學報,即将發表

  • 新浪企業微博口碑傳播的實證研究(與張晶,黃京華,嚴威合作),BETVLCTOR伟德官方网站學報(自然科學版), 54卷,第5期,649-654,2014

  • ERP實施對企業績效影響的實證研究——基于傾向性得分匹配法 (與張露,黃京華合作),BETVLCTOR伟德官方网站學報(自然科學版), 53卷,第1期,2013

  • 人力資本對我國區域創新及經濟增長的影響_基于空間計量的實證研究 (與錢曉烨,遲巍合作),數量經濟技術經濟研究, 107-121,第4期, 2010

  • 基于收入分布的收入差距擴大成因的分解(與遲巍,餘秋梅合作),數量經濟技術經濟研究,52-64,第9期,2008

  • 一種新的收入差距研究的計量方法_基于分布函數的半參數化估計(與遲巍,餘秋梅合作),數量經濟技術經濟研究,119-129,第8期, 2007


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