This course focuses on the linear model techniques adopted for the analysis of a typical micro panel-data set with a large number of individuals and a small number of time periods. Such techniques ...

Abstract: For a relatively small labeled dataset from high-dimensional generalized linear models with block-wise missing covariates and a large unlabeled dataset, we utilize a model-assisted approach ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

In microbiome studies, addressing the unique characteristics of sequence data—such as compositionality, zero inflation, overdispersion, high dimensionality, and non-normality—is crucial for accurate ...

ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...

Generalized linear bandits have been extensively studied due to their broad applicability in real-world online decision-making problems. However, these methods typically assume that the expected ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...