6 papers · 1 filter
Normal approximations in nonparametric empirical Bayes
Jiafeng Chen, Nabarun Deb, Nikolaos Ignatiadis
Empirical Bayes analyses routinely model noisy measurements of latent parameters as normal, justifying this by an informal appeal to the central limit theorem (CLT). This paper put…
Parametric Mean-Field empirical Bayes in high-dimensional linear regression
Seunghyun Lee, Nabarun Deb
In this paper, we consider the problem of parametric empirical Bayes estimation of an i.i.d. prior in high-dimensional Bayesian linear regression, with random design. We obtain the…
Pivotal CLTs for Pseudolikelihood via Conditional Centering in Dependent Random Fields
Nabarun Deb
In this paper, we study fluctuations of conditionally centered statistics of the form where $(Ï_1,\ldots ,…
CLT in high-dimensional Bayesian linear regression with low SNR
Seunghyun Lee, Nabarun Deb, Sumit Mukherjee
We study central limit theorems for linear statistics in high-dimensional Bayesian linear regression with product priors. Unlike the existing literature where the focus is on poste…
Phase Transition in Nonparametric Minimax Rates for Covariate Shifts on Approximate Manifolds
Yuyao Wang, Nabarun Deb, Debarghya Mukherjee
We study nonparametric regression under covariate shift with structured data, where a small amount of labeled target data is supplemented by a large labeled source dataset. In many…
Distribution-free Measures of Association based on Optimal Transport
Nabarun Deb, Promit Ghosal, Bodhisattva Sen
In this paper we propose and study a class of nonparametric, yet interpretable measures of association between two random vectors and taking values in an…