3 papers
cs.LG2023
Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features
Hangbin Lee, Il Do Ha, Changha Hwang +1
There is a growing interest in subject-specific predictions using deep neural networks (DNNs) because real-world data often exhibit correlations, which has been typically overlooke…
stat.ME2023
Point Mass in the Confidence Distribution: Is it a Drawback or an Advantage?
Hangbin Lee, Youngjo Lee
Stein's (1959) problem highlights the phenomenon called the probability dilution in high dimensional cases, which is known as a fundamental deficiency in probabilistic inference. T…
stat.ML2023
Deep Neural Networks for Semiparametric Frailty Models via H-likelihood
Hangbin Lee, IL DO HA, Youngjo Lee
For prediction of clustered time-to-event data, we propose a new deep neural network based gamma frailty model (DNN-FM). An advantage of the proposed model is that the joint maximi…