My research is supported by the grant CAREER Award DMS-1941945 and DMS-1854637 from the National Science Foundation.

Manuscript under Review

Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference
Huijie Feng, Yang Ning, Jiwei Zhao
Submitted, 2021. [Arxiv]

Optimal and Safe Estimation for High-dimensional Semi-supervised Learning
Siyi Deng, Yang Ning, Jiwei Zhao, Heping Zhang
Submitted, 2020. [Arxiv]

Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data
Yanxin Jin, Yang Ning, Keanming Tan
Submitted, 2020. [Arxiv]

Sparse Confidence Sets for Normal Mean Models
Yang Ning, Guang Cheng
Submitted, 2020. [Arxiv]

Nonregular and Minimax Estimation of Individualized Thresholds in High dimension with Binary Responses 
Huijie Feng, Yang Ning, Jiwei Zhao
Submitted, 2019. [Arxiv]

Improving Covariate Balancing Propensity Score: A Doubly Robust and Efficient Approach
Jianqing Fan, Kosuke Imai, Han Liu, Yang Ning, Xiaolin Yang
Submitted, 2016. [PDF] [R package]

Local and Global Inference for High Dimensional Gaussian Copula Graphical Models 
Quanquan Gu, Yuan Cao, Yang Ning, Han Liu
Submitted, 2015. [Arxiv]

Journal and Conference

Adaptive Estimation of Multivariate Regression with Hidden Variables
Xin Bing, Yang Ning, Yaosheng Xu
The Annals of Statistics, 2021. [Arxiv]

Heterogeneity-aware and Communication-efficient Distributed Statistical Inference 
Rui Duan, Yang Ning, Yong Chen
Biometrika, 2021. [Arxiv]

Regression Discontinuity Design under Self-selection 
Sida Peng, Yang Ning
AISTAT, 2021. [Arxiv]

Optimal Sampling for Generalized Linear Models under Measurement Constraints 
Tao Zhang, Yang Ning, David Ruppert
Journal of Computational and Graphical Statistics, 2020+. [Arxiv]

On Specification Tests for Composite Likelihood Inference 
Jing Huang, Yang Ning, Nancy Reid, Yong Chen
Biometrika, 2020+.

High-Dimensional Inference for Cluster-Based Graphical Models 
Carson Eisenach, Florentina Bunea, Yang Ning, Claudiu Dinicu
Journal of Machine Learning Research, 2020. [PDF]

Robust Estimation of Causal Effect via High Dimensional Covariate Balancing Propensity Score
Yang Ning, Sida Peng, Kosuke Imai
Biometrika, 2019+. [Arxiv] [R package]

Test of Significance for High-dimensional Longitudinal Data 
Ethan X. Fang, Yang Ning, Runze Li
The Annals of Statistics, 2019+.

Adaptive Estimation in Structured Factor Models with Application to Overlapping Clustering
Xin Bing, Florentina Bunea, Yang Ning, Marten Wegkamp
The Annals of Statistics, 2019. [Arxiv] [Code]

Efficient Augmentation and Relaxation Learning for Individualized Treatment Rules using Observational Data
Yingqi Zhao, Eric Laber, Yang Ning, Sumona Saha, and Bruce Sands
Journal of Machine Learning Research, 2019. [PDF][R package]

High-dimensional Mixed Graphical Model with Ordinal Data: Parameter Estimation and Statistical Inference
Huijie Feng, Yang Ning
AISTATS, 2019. [PDF]

On Semiparametric Exponential Family Graphical Models
Zhuoran Yang, Yang Ning, Han Liu
Journal of Machine Learning Research, 2018. [PDF]

A Unified Theory of Confidence Regions and Testing for High Dimensional Estimating Equations
Matey Neykov, Yang Ning, Jun Liu, Han Liu
Statistical Science, 2018. [PDF]

A Conditional Composite Likelihood Ratio Test with Boundary Constraints
Yong Chen, Jing Huang, Yang Ning, Kung-Yee Liang, Bruce Lindsay
Biometrika, 2018. [PDF]

Testing and Confidence Intervals for High Dimensional Proportional Hazards Model
Ethan X. Fang, Yang Ning, Han Liu
Journal of Royal Statistical Society, Series B, 2017. [PDF][Code]

A Class of Weighted Estimating Equations for Semiparametric Transformation Models with Missing Covariates
Yang Ning, Grace Yi, Nancy Reid
Scandinavian Journal of Statistics, 2017. [PDF]

PLEMT: A Novel Pseudolikelihood Based EM Test for Homogeneity in Generalized Exponential Tilt Mixture Models
Chuan Hong, Yang Ning, Shuang Wang, Hao Wu, Raymond Carroll, Yong Chen
Journal of the American Statistical Association, 2017. [PDF] [R package]

On the Pseudolikelihood Inference for Semiparametric Models with Boundary Problems
Yong Chen, Jing Ning, Yang Ning, Kung-Yee Liang, Karen Bandeen-Roche
Biometrika, 2017. [PDF]

A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models
Yang Ning, Han Liu
The Annals of Statistics, 2017. [PDF] [R package]

Replicates in High Dimensions, with Applications to Latent Variable Graphical Models
Keanming Tan, Yang Ning, Daniela Witten, Han Liu
Biometrika, 2016. [PDF]

High Dimensional Semiparametric Latent Graphical Model for Mixed Data
Jianqing Fan, Han Liu, Yang Ning, Hui Zou
Journal of Royal Statistical Society, Series B, 2016. [PDF]

A Likelihood Ratio Framework for High Dimensional Semiparametric Inference
Yang Ning, Tianqi Zhao, Han Liu
The Annals of Statistics, 2017. [PDF]

High Dimensional Expectation-Maximization Algorithm: Statistical Optimization and Asymptotic Normality
Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu
NIPS, 2015. [PDF]

Estimation of Covariate-specific Time-dependent ROC Curves in the Presence of Missing Biomarkers
Shanshan Li, Yang Ning
Biometrics, 2015. [PDF]

A Class of Pseudolikelihood Ratio Tests for Homogeneity in Exponential Tilt Mixture Models
Yang Ning, Yong Chen
Scandinavian Journal of Statistics, 2015. [PDF]

Semiparametric Tests for Identifying Differentially Methylated Loci With Case–Control Designs Using Illumina Arrays
Yong Chen, Yang Ning, Chuan Hong, Shuang Wang
Genetic Epidemiology, 2014. [PDF]

Reducing the Sensitivity to Nuisance Parameters in Pseudo-Likelihood Functions
Yang Ning, Kung-Yee Liang, Nancy Reid
Canadian Journal of Statistics, 2014. [PDF]

High-dimensional Semiparametric Bigraphical Models
Yang Ning, Han Liu
Biometrika, 2013. [PDF]

Differential Principal Component Analysis of ChIP-seq
Hongkai Ji, Xia Li, Qian-fei Wang, Yang Ning
Proceedings of the National Academy of Sciences, 2013. [PDF]