246 citations · 277 across the 8 of their papers we have counts for
9 papers
Valid Bayesian Inference based on Variance Weighted Projection for High-Dimensional Logistic Regression with Binary Covariates
Abhishek Ojha, Naveen N. Narisetty
We address the challenge of conducting inference for a categorical treatment effect related to a binary outcome variable while taking into account high-dimensional baseline covaria…
Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit
Ke Li, Yun Yang, Naveen N. Narisetty
In this paper, we consider the multi-armed bandit problem with high-dimensional features. First, we prove a minimax lower bound, $\mathcal{O}\big((\log d)^{\frac{α+1}{2}}T^{\frac{1…
Identifying regions of inhomogeneities in spatial processes via an M-RA and mixture priors
Marco H. Benedetti, Veronica J. Berrocal, Naveen N. Narisetty
Soils have been heralded as a hidden resource that can be leveraged to mitigate and address some of the major global environmental challenges. Specifically, the organic carbon stor…
A Hierarchical Integrative Group LASSO (HiGLASSO) Framework for Analyzing Environmental Mixtures
Jonathan Boss, Alexander Rix, Yin-Hsiu Chen +6
Environmental health studies are increasingly measuring multiple pollutants to characterize the joint health effects attributable to exposure mixtures. However, the underlying dose…
Evaluating proxy influence in assimilated paleoclimate reconstructions -- Testing the exchangeability of two ensembles of spatial processes
Trevor Harris, Bo Li, Nathan Steiger +3
Climate field reconstructions (CFR) attempt to estimate spatiotemporal fields of climate variables in the past using climate proxies such as tree rings, ice cores, and corals. Data…
New methods for multiple testing in permutation inference for the general linear model
Tomas Mrkvicka, Mari Myllymaki, Mikko Kuronen +1
Permutation methods are commonly used to test significance of regressors of interest in general linear models (GLMs) for functional (image) data sets, in particular for neuroimagin…
Bayesian Regularization for Graphical Models with Unequal Shrinkage
Lingrui Gan, Naveen N. Narisetty, Feng Liang
We consider a Bayesian framework for estimating a high-dimensional sparse precision matrix, in which adaptive shrinkage and sparsity are induced by a mixture of Laplace priors. Bes…
Extremal Depth for Functional Data and Applications
Naveen N. Narisetty, Vijayan N. Nair
We propose a new notion called `extremal depth' (ED) for functional data, discuss its properties, and compare its performance with existing concepts. The proposed notion is based o…
Bayesian variable selection with shrinking and diffusing priors
Naveen Naidu Narisetty, Xuming He
We consider a Bayesian approach to variable selection in the presence of high dimensional covariates based on a hierarchical model that places prior distributions on the regression…