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07/05/2023
High-Dimensional Expected Shortfall Regression
The expected shortfall is defined as the average over the tail below (or...
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03/22/2023
Estimation of Complier Expected Shortfall Treatment Effects with a Binary Instrumental Variable
Estimating the causal effect of a treatment or exposure for a subpopulat...
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12/11/2022
Robust Estimation and Inference for Expected Shortfall Regression with Many Regressors
Expected Shortfall (ES), also known as superquantile or Conditional Valu...
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12/11/2022
Retire: Robust Expectile Regression in High Dimensions
High-dimensional data can often display heterogeneity due to heterosceda...
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10/23/2022
Scalable estimation and inference for censored quantile regression process
Censored quantile regression (CQR) has become a valuable tool to study t...
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09/07/2022
High-dimensional Inference for Generalized Linear Models with Hidden Confounding
Statistical inferences for high-dimensional regression models have been ...
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05/05/2022
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression
Penalized quantile regression (QR) is widely used for studying the relat...
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10/25/2021
Communication-Efficient Distributed Quantile Regression with Optimal Statistical Guarantees
We address the problem of how to achieve optimal inference in distribute...
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09/12/2021
High-Dimensional Quantile Regression: Convolution Smoothing and Concave Regularization
â„“_1-penalized quantile regression is widely used for analyzing high-dime...
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12/09/2020
Smoothed Quantile Regression with Large-Scale Inference
Quantile regression is a powerful tool for learning the relationship bet...
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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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05/15/2020
Model Linkage Selection for Cooperative Learning
Rapid developments in data collecting devices and computation platforms ...
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06/23/2019
Robust convex clustering: How does fusion penalty enhance robustness?
Convex clustering has gained popularity recently due to its desirable pe...
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05/28/2019
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks
Neuroscientists have enjoyed much success in understanding brain functio...
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10/18/2018
Distributionally Robust Reduced Rank Regression and Principal Component Analysis in High Dimensions
We propose robust sparse reduced rank regression and robust sparse princ...
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09/17/2018
A convex formulation for high-dimensional sparse sliced inverse regression
Sliced inverse regression is a popular tool for sufficient dimension red...
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06/04/2017
Graphical Nonconvex Optimization for Optimal Estimation in Gaussian Graphical Models
We consider the problem of learning high-dimensional Gaussian graphical ...
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04/29/2016
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via Truncated Rayleigh Flow
Sparse generalized eigenvalue problem plays a pivotal role in a large fa...
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05/16/2014
Selection Bias Correction and Effect Size Estimation under Dependence
We consider large-scale studies in which it is of interest to test a ver...
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02/28/2014
Learning Graphical Models With Hubs
We consider the problem of learning a high-dimensional graphical model i...
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07/19/2013
