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08/31/2022
Two-stage Hypothesis Tests for Variable Interactions with FDR Control
In many scenarios such as genome-wide association studies where dependen...
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07/29/2022
Treatment Effect Estimation with Unobserved and Heterogeneous Confounding Variables
The estimation of the treatment effect is often biased in the presence o...
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01/20/2022
Inference in High-dimensional Multivariate Response Regression with Hidden Variables
This paper studies the inference of the regression coefficient matrix un...
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12/24/2021
Optimal Variable Clustering for High-Dimensional Matrix Valued Data
Matrix valued data has become increasingly prevalent in many application...
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08/09/2021
Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference
This work is motivated by learning the individualized minimal clinically...
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08/03/2021
Optimal Covariate Balancing Conditions in Propensity Score Estimation
Inverse probability of treatment weighting (IPTW) is a popular method fo...
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03/23/2021
On the global identifiability of logistic regression models with misclassified outcomes
In the last decade, the secondary use of large data from health systems,...
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12/09/2020
Exponential Family Graphical Models: Correlated Replicates and Unmeasured Confounders, with Applications to fMRI Data
Graphical models have been used extensively for modeling brain connectiv...
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11/28/2020
Optimal Semi-supervised Estimation and Inference for High-dimensional Linear Regression
There are many scenarios such as the electronic health records where the...
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09/07/2020
Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data
This paper proposes a doubly robust two-stage semiparametric difference-...
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08/17/2020
Sparse Confidence Sets for Normal Mean Models
In this paper, we propose a new framework to construct confidence sets f...
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07/08/2020
Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score
With the increasing adoption of electronic health records, there is an i...
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03/30/2020
Adaptive Estimation of Multivariate Regression with Hidden Variables
This paper studies the estimation of the coefficient matrix in multivar...
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02/17/2020
Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness
Recently smoothing deep neural network based classifiers via isotropic G...
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12/20/2019
Heterogeneity-aware and communication-efficient distributed statistical inference
In multicenter research, individual-level data are often protected again...
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11/21/2019
Regression Discontinuity Design under Self-selection
In Regression Discontinuity (RD) design, self-selection leads to differe...
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07/17/2019
Optimal Sampling for Generalized Linear Models under Measurement Constraints
Suppose we are using a generalized linear model to predict a scalar outc...
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05/26/2019
Nonregular and Minimax Estimation of Individualized Thresholds in High Dimension with Binary Responses
Given a large number of covariates Z, we consider the estimation of a hi...
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01/03/2019
Efficient augmentation and relaxation learning for individualized treatment rules using observational data
Individualized treatment rules aim to identify if, when, which, and to w...
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12/20/2018
Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score
In this paper, we propose a robust method to estimate the average treatm...
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06/13/2018
High-Dimensional Inference for Cluster-Based Graphical Models
Motivated by modern applications in which one constructs graphical model...
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04/23/2017
Sparse Latent Factor Models with Pure Variables for Overlapping Clustering
The problem of overlapping variable clustering, ubiquitous in data scien...
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10/30/2015
A Unified Theory of Confidence Regions and Testing for High Dimensional Estimating Equations
We propose a new inferential framework for constructing confidence regio...
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02/09/2015
Local and Global Inference for High Dimensional Nonparanormal Graphical Models
This paper proposes a unified framework to quantify local and global inf...
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12/30/2014
A General Theory of Hypothesis Tests and Confidence Regions for Sparse High Dimensional Models
We consider the problem of uncertainty assessment for low dimensional co...
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12/30/2014
High Dimensional Expectation-Maximization Algorithm: Statistical Optimization and Asymptotic Normality
We provide a general theory of the expectation-maximization (EM) algorit...
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12/30/2014
On Semiparametric Exponential Family Graphical Models
We propose a new class of semiparametric exponential family graphical mo...
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12/16/2014
Testing and Confidence Intervals for High Dimensional Proportional Hazards Model
This paper proposes a decorrelation-based approach to test hypotheses an...
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12/06/2014
A Likelihood Ratio Framework for High Dimensional Semiparametric Regression
We propose a likelihood ratio based inferential framework for high dimen...
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04/29/2014
