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07/31/2023
Forster-Warmuth Counterfactual Regression: A Unified Learning Approach
Series or orthogonal basis regression is one of the most popular non-par...
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07/11/2023
Semiparametric Shape-restricted Estimators for Nonparametric Regression
Estimating the conditional mean function that relates predictive covaria...
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07/03/2023
Inference for Projection Parameters in Linear Regression: beyond d = o(n^1/2)
We consider the problem of inference for projection parameters in linear...
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06/26/2023
Central Limit Theorems and Approximation Theory: Part II
In Part I of this article (Banerjee and Kuchibhotla (2023)), we have int...
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06/25/2023
Dual Induction CLT for High-dimensional m-dependent Data
In this work, we provide a 1/√(n)-rate finite sample Berry-Esseen bound ...
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04/25/2023
Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation
We study subsampling-based ridge ensembles in the proportional asymptoti...
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04/12/2023
Post-selection Inference for Conformal Prediction: Trading off Coverage for Precision
Conformal inference has played a pivotal role in providing uncertainty q...
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02/27/2023
Extrapolated cross-validation for randomized ensembles
Ensemble methods such as bagging and random forests are ubiquitous in fi...
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02/08/2023
Tight Concentration Inequality for Sub-Weibull Random Variables with Generalized Bernstien Orlicz norm
Recent development in high-dimensional statistical inference has necessi...
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12/10/2022
High-dimensional Berry-Esseen Bound for m-Dependent Random Samples
In this work, we provide a (n/m)^-1/2-rate finite sample Berry-Esseen bo...
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10/20/2022
Bagging in overparameterized learning: Risk characterization and risk monotonization
Bagging is a commonly used ensemble technique in statistics and machine ...
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06/07/2022
Median Regularity and Honest Inference
We introduce a new notion of regularity of an estimator called median re...
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05/25/2022
Mitigating multiple descents: A model-agnostic framework for risk monotonization
Recent empirical and theoretical analyses of several commonly used predi...
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03/03/2022
Doubly Robust Calibration of Prediction Sets under Covariate Shift
Conformal prediction has received tremendous attention in recent years a...
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11/17/2021
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Optimal Transport and Conformal Prediction Sets
In the United States and elsewhere, risk assessment algorithms are being...
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06/21/2021
maars: Tidy Inference under the 'Models as Approximations' Framework in R
Linear regression using ordinary least squares (OLS) is a critical part ...
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06/01/2021
Median bias of M-estimators
In this note, we derive bounds on the median bias of univariate M-estima...
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05/30/2021
The HulC: Confidence Regions from Convex Hulls
We develop and analyze the HulC, an intuitive and general method for con...
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04/28/2021
Finite-sample Efficient Conformal Prediction
Conformal prediction is a generic methodology for finite-sample valid di...
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09/28/2020
High-dimensional CLT for Sums of Non-degenerate Random Vectors: n^-1/2-rate
In this note, we provide a Berry–Esseen bounds for rectangles in high-di...
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08/26/2020
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets
Risk assessment algorithms have been correctly criticized for potential ...
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07/19/2020
Berry-Esseen Bounds for Projection Parameters and Partial Correlations with Increasing Dimension
The linear regression model can be used even when the true regression fu...
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06/09/2020
Near-Optimal Confidence Sequences for Bounded Random Variables
Many inference problems, such as sequential decision problems like A/B t...
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05/13/2020
Exchangeability, Conformal Prediction, and Rank Tests
Conformal prediction has been a very popular method of distribution-free...
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09/13/2018
Deterministic Inequalities for Smooth M-estimators
Ever since the proof of asymptotic normality of maximum likelihood estim...
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06/23/2018
Assumption Lean Regression
It is well known that models used in conventional regression analysis ar...
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06/16/2018
Cramér-type Large deviation and non-uniform central limit theorems in high dimensions
Central limit theorems (CLTs) for high-dimensional random vectors with d...
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06/11/2018
Valid Post-selection Inference in Assumption-lean Linear Regression
Construction of valid statistical inference for estimators based on data...
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04/08/2018
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics: Applications in Covariance Estimation and Linear Regression
Concentration inequalities form an essential toolkit in the study of hig...
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02/15/2018