Arun Kumar Kuchibhotla

research

∙ 07/31/2023

Forster-Warmuth Counterfactual Regression: A Unified Learning Approach

Series or orthogonal basis regression is one of the most popular non-par...

0 Yachong Yang, et al. ∙

research

∙ 07/11/2023

Semiparametric Shape-restricted Estimators for Nonparametric Regression

Estimating the conditional mean function that relates predictive covaria...

0 Kenta Takatsu, et al. ∙

research

∙ 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...

0 Woonyoung Chang, et al. ∙

research

∙ 06/26/2023

Central Limit Theorems and Approximation Theory: Part II

In Part I of this article (Banerjee and Kuchibhotla (2023)), we have int...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 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 ...

0 Heejong Bong, et al. ∙

research

∙ 04/25/2023

Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation

We study subsampling-based ridge ensembles in the proportional asymptoti...

0 Jin-Hong Du, et al. ∙

research

∙ 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...

0 Siddhaarth Sarkar, et al. ∙

research

∙ 02/27/2023

Extrapolated cross-validation for randomized ensembles

Ensemble methods such as bagging and random forests are ubiquitous in fi...

0 Jin-Hong Du, et al. ∙

research

∙ 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...

0 Heejong Bong, et al. ∙

research

∙ 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...

0 Heejong Bong, et al. ∙

research

∙ 10/20/2022

Bagging in overparameterized learning: Risk characterization and risk monotonization

Bagging is a commonly used ensemble technique in statistics and machine ...

0 Pratik Patil, et al. ∙

research

∙ 06/07/2022

Median Regularity and Honest Inference

We introduce a new notion of regularity of an estimator called median re...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 05/25/2022

Mitigating multiple descents: A model-agnostic framework for risk monotonization

Recent empirical and theoretical analyses of several commonly used predi...

0 Pratik Patil, et al. ∙

research

∙ 03/03/2022

Doubly Robust Calibration of Prediction Sets under Covariate Shift

Conformal prediction has received tremendous attention in recent years a...

0 Yachong Yang, et al. ∙

research

∙ 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...

0 Richard A. Berk, et al. ∙

research

∙ 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 ...

0 Riccardo Fogliato, et al. ∙

research

∙ 06/01/2021

Median bias of M-estimators

In this note, we derive bounds on the median bias of univariate M-estima...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 05/30/2021

The HulC: Confidence Regions from Convex Hulls

We develop and analyze the HulC, an intuitive and general method for con...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 04/28/2021

Finite-sample Efficient Conformal Prediction

Conformal prediction is a generic methodology for finite-sample valid di...

0 Yachong Yang, et al. ∙

research

∙ 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...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 08/26/2020

Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets

Risk assessment algorithms have been correctly criticized for potential ...

0 Richard A. Berk, et al. ∙

research

∙ 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...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 06/09/2020

Near-Optimal Confidence Sequences for Bounded Random Variables

Many inference problems, such as sequential decision problems like A/B t...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 05/13/2020

Exchangeability, Conformal Prediction, and Rank Tests

Conformal prediction has been a very popular method of distribution-free...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 09/13/2018

Deterministic Inequalities for Smooth M-estimators

Ever since the proof of asymptotic normality of maximum likelihood estim...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 06/23/2018

Assumption Lean Regression

It is well known that models used in conventional regression analysis ar...

0 Richard Berk, et al. ∙

research

∙ 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...

0 Debapratim Banerjee, et al. ∙

research

∙ 06/11/2018

Valid Post-selection Inference in Assumption-lean Linear Regression

Construction of valid statistical inference for estimators based on data...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 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...

0 Arun Kumar Kuchibhotla, et al. ∙

research

∙ 02/15/2018

A Model Free Perspective for Linear Regression: Uniform-in-model Bounds for Post Selection Inference

For the last two decades, high-dimensional data and methods have prolife...

0 Arun Kumar Kuchibhotla, et al. ∙

Arun Kumar Kuchibhotla

Featured Co-authors