28 citations · 28 across the 7 of their papers we have counts for
7 papers
Statistical Optimality of Prediction-Powered Inference
Se Yoon Lee, Jae Kwang Kim
The prediction-powered inference (PPI) proposed by Angelopoulos et al. (2023) is a popular method that leverages a small number of labeled samples and machine learning predictions…
MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation
Se Yoon Lee, Jae Kwang Kim
Obtaining high-quality labels is costly, whereas unlabeled covariates are often abundant, motivating semi-supervised inference methods with reliable uncertainty quantification. Pre…
Using Bayesian Statistics in Confirmatory Clinical Trials in the Regulatory Setting
Se Yoon Lee
Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatm…
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of intere…
Gibbs sampler and coordinate ascent variational inference: a set-theoretical review
Se Yoon Lee
One of the fundamental problems in Bayesian statistics is the approximation of the posterior distribution. Gibbs sampler and coordinate ascent variational inference are renownedly…
Tail-adaptive Bayesian shrinkage
Se Yoon Lee, Peng Zhao, Debdeep Pati +1
Robust Bayesian methods for high-dimensional regression problems under diverse sparse regimes are studied. Traditional shrinkage priors are primarily designed to detect a handful o…