In conventional statistical and machine learning methods, it is typicall...
Mendelian randomization (MR) is a powerful method that uses genetic vari...
We consider Q-learning with knowledge transfer, using samples from a tar...
Existing high-dimensional statistical methods are largely established fo...
Machine learning algorithms typically assume that training and test exam...
The limited representation of minorities and disadvantaged populations i...
In this paper, the performance of a dual-hop relaying terahertz (THz)
wi...
Genome-wide association studies (GWAS) have identified thousands of gene...
In this paper, we investigate the performance of a mixed
radio-frequency...
In this paper, we investigate the performance of a reconfigurable intell...
In this paper, we study a dual-hop mixed power line communication and
ra...
Transfer learning for high-dimensional Gaussian graphical models (GGMs) ...
Instrumental variable methods are widely used for inferring the causal e...
This paper considers the estimation and prediction of a high-dimensional...
Linear mixed-effects models are widely used in analyzing clustered or
re...
In this paper, we prove that under proper conditions, bootstrap can furt...