Distribution-Free, Risk-Controlling Prediction Sets, Stephen Bates, Anastasios Angelopoulos, Lihua Lei, Jitendra Malik, and Michael I. Jordan, 2021. To appear in Journal of the ACM. Arxiv
Smoothed Nested Testing on Directed Acyclic Graphs, Jackson H. Loper, Lihua Lei, William Fithian, and Wesley Tansey, 2021. To appear in Biometrika. Arxiv
Conformal Inference of Counterfactuals and Individual Treatment Effects, Lihua Lei, and Emmanuel Candès, 2021. To appear in Journal of the Royal Statistical Society: Series B (JRSS-B). Arxiv
Regression adjustment in randomized experiments with a diverging number of covariates, Lihua Lei, and Peng Ding, 2020. To appear in Biometrika. Arxiv
Hierarchical community detection by recursive partitioning, Tianxi Li, Lihua Lei, Sharmodeep Bhattacharyya, Purnamrita Sarkar, Peter J. Bickel, and Elizaveta Levina, 2020. To appear in Journal of the American Statistical Association (JASA). Arxiv
An Assumption-Free Exact Test For Fixed-Design Linear Models With Exchangeable Errors, Lihua Lei, and Peter J. Bickel, 2020. Biometrika 108 (2021), 397-412. Arxiv
A general interactive framework for FDR control under structural constraints, Lihua Lei, Aaditya Ramdas, and William Fithian, 2020. Biometrika 108 (2021), 253-267. Arxiv
On the Adaptivity of Stochastic Gradient-Based Optimization, Lihua Lei, and Michael I. Jordan, 2020. SIAM Journal on Optimization (SIOPT) 30 (2020), 1473-1500. Arxiv
Overlap in Observational Studies With High-Dimensional Covariates, Alexander D'Amour, Peng Ding, Avi Feller, Lihua Lei, and Jasjeet Sekhon, 2019. Journal of Econometrics (JoE) 221 (2019), 644-654. Arxiv
AdaPT: An interactive procedure for multiple testing with side information, Lihua Lei, and William Fithian, 2018. Journal of the Royal Statistical Society: Series B (JRSS-B) 80 (2018), 649-679. Arxiv
Asymptotics For High Dimensional Regression M-Estimates: Fixed Design Results, Lihua Lei, Peter J. Bickel, and Noureddine El Karoui. Probability Theory and Related Fields (PTRF), 172 (2018), 983-1079. Arxiv
Functional Coefficient Moving Average Model With Applications To Forecasting Chinese CPI, Song Xi Chen, Lihua Lei, and Yundong Tu. Statistica Sinica 26 (2016), 1649-1672.
Variance Reduction with Sparse Gradients, Melih Elibol, Lihua Lei, Michael I. Jordan, International Conference on Learning Representations (ICLR), 2020.
HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step, Yuting Ye, Lihua Lei, and Cheng Ju, International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.
Nonconvex Finite-Sum Optimization Via SCSG Methods, Lihua Lei, Cheng Ju, Jianbo Chen, and Michael I. Jordan. Advances in Neural Information Processing Systems (NIPS), 2017. Arxiv
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method, Lihua Lei, and Michael I. Jordan. International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. Arxiv (The Arxiv version adds an erratum for the AISTATS camera-ready version)
Power of Ordered Hypothesis Testing, Lihua Lei, and William Fithian. International Conference on Machine Learning (ICML), 2016. Arxiv
Double-Robust Two-Way-Fixed-Effects Regression For Panel Data, Dmitry Arkhangelsky, Guido W. Imbens, Lihua Lei, and Xiaoman Luo, 2021.
BONuS: Multiple multivariate testing with a data-adaptivetest statistic, Chiao-Yu Yang, Lihua Lei, Nhat Ho, and William Fithian, 2021.
Testing for Outliers with Conformal p-values, Stephen Bates, Emmanuel Candès, Lihua Lei, Yaniv Romano, and Matteo Sesia, 2021. UDL slides
Conformalized Survival Analysis, Emmanuel Candès, Lihua Lei, and Zhimei Ren, 2021.
Conditional calibration for false discovery rate control under dependence, William Fithian, and Lihua Lei, 2020.
Consistency of Spectral Clustering on Hierarchical Stochastic Block Models, Lihua Lei, Xiaodong Li, and Xingmei Lou, 2020.
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization, Samuel Horváth, Lihua Lei, Peter Richtárik, and Michael I. Jordan, 2020.
Unified Two-to-infinity Eigenspace Perturbation Theory for Symmetric Random Matrices, Lihua Lei, 2019.
adaptMT, an R package for AdaPT (adaptive p-value thresholding) on CRAN
A short demo
A long tutorial
mkn, an R package for multiple-knockoffs based inference (an ongoing project)
cfcausal, an R package for conformal inference of counterfactuals and individual treatment effects
dbh, an R package for dependence-adjusted Benjamini-Hochberg and general step-up procedures