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05/22/2023
Semi-Supervised Causal Inference: Generalizable and Double Robust Inference for Average Treatment Effects under Selection Bias with Decaying Overlap
Average treatment effect (ATE) estimation is an essential problem in the...
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11/12/2021
Dynamic treatment effects: high-dimensional inference under model misspecification
This paper considers the inference for heterogeneous treatment effects i...
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10/10/2021
High-dimensional Inference for Dynamic Treatment Effects
This paper proposes a confidence interval construction for heterogeneous...
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04/14/2021
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying Overlap
Semi-supervised (SS) inference has received much attention in recent yea...
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03/21/2021
Comments on Leo Breiman's paper 'Statistical Modeling: The Two Cultures' (Statistical Science, 2001, 16(3), 199-231)
Breiman challenged statisticians to think more broadly, to step into the...
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03/01/2021
Dynamic covariate balancing: estimating treatment effects over time
This paper discusses the problem of estimation and inference on time-var...
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02/01/2021
Learning to Combat Noisy Labels via Classification Margins
A deep neural network trained on noisy labels is known to quickly lose i...
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07/26/2020
DeepHazard: neural network for time-varying risks
Prognostic models in survival analysis are aimed at understanding the re...
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06/12/2020
Detangling robustness in high dimensions: composite versus model-averaged estimation
Robust methods, though ubiquitous in practice, are yet to be fully under...
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05/25/2020
Fair Policy Targeting
One of the major concerns of targeting interventions on individuals in s...
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01/08/2020
Censored Quantile Regression Forest
Random forests are powerful non-parametric regression method but are sev...
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12/27/2019
Minimax Semiparametric Learning With Approximate Sparsity
Many objects of interest can be expressed as a linear, mean square conti...
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06/29/2019
Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates
Estimating causal effects for survival outcomes in the high-dimensional ...
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05/02/2019
Sparsity Double Robust Inference of Average Treatment Effects
Many popular methods for building confidence intervals on causal effects...
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04/02/2019
Synthetic learner: model-free inference on treatments over time
Understanding of the effect of a particular treatment or a policy pertai...
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02/08/2019
Censored Quantile Regression Forests
Random forests are powerful non-parametric regression method but are sev...
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02/02/2019
High-dimensional semi-supervised learning: in search for optimal inference of the mean
We provide a high-dimensional semi-supervised inference framework focuse...
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03/03/2018
Confidence intervals for high-dimensional Cox models
The purpose of this paper is to construct confidence intervals for the r...
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02/26/2018
Testability of high-dimensional linear models with non-sparse structures
This paper studies hypothesis testing and confidence interval constructi...
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08/14/2017
Fixed effects testing in high-dimensional linear mixed models
Many scientific and engineering challenges -- ranging from pharmacokinet...
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08/01/2017
Breaking the curse of dimensionality in regression
Models with many signals, high-dimensional models, often impose structur...
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07/29/2017
Fine-Gray competing risks model with high-dimensional covariates: estimation and Inference
The purpose of this paper is to construct confidence intervals for the r...
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05/06/2017
Comments on `High-dimensional simultaneous inference with the bootstrap'
We provide comments on the article "High-dimensional simultaneous infere...
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05/02/2017
A projection pursuit framework for testing general high-dimensional hypothesis
This article develops a framework for testing general hypothesis in high...
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02/20/2017
Uniform Inference for High-dimensional Quantile Regression: Linear Functionals and Regression Rank Scores
Hypothesis tests in models whose dimension far exceeds the sample size c...
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10/14/2016
Two-sample testing in non-sparse high-dimensional linear models
In analyzing high-dimensional models, sparsity of the model parameter is...
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10/10/2016
Linear Hypothesis Testing in Dense High-Dimensional Linear Models
We propose a methodology for testing linear hypothesis in high-dimension...
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10/07/2016
Significance testing in non-sparse high-dimensional linear models
In high-dimensional linear models, the sparsity assumption is typically ...
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09/22/2016
Robust Confidence Intervals in High-Dimensional Left-Censored Regression
This paper develops robust confidence intervals in high-dimensional and ...
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10/05/2015
Boosting in the presence of outliers: adaptive classification with non-convex loss functions
This paper examines the role and efficiency of the non-convex loss funct...
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07/31/2015
