IL DO HA

Professor

Pusan National University

South Korea

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IL DO HA is a Professor at Pukyong National University in South Korea. His research interests include deep learning, statistical regression modeling, and survival analysis, as evidenced by his recent publications on neural networks, likelihood-based inference, and competing-risks data. He investigates the intersection of advanced statistical methods and machine learning techniques to enhance various applications, including smart farming and control chart methodologies.

IL DO HA

Research Interests

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Articles (16)

Fitting deep neural networks into the statistical regression modelling setting

Joint AFT random-effect modeling approach for clustered competing-risks data

Semiparametric accelerated failure time models under unspecified random effect distributions

A Study on the Relationship Between Deep Learning and Statistical Models

Likelihood-Based Inference of Log-Logistic Accelerated Hazards Regression Models for Cross Hazards Data

A Smart Farm DNN Survival Model Considering Tomato Farm Effect

Penalized variable selection in multi-parameter regression survival modeling

Deep learning-based residual control chart for count data

Application of Deep Learning and Neural Network to Speeding Ticket and Insurance Claim Count Data

Flexible parametric copula modeling approaches for clustered survival data

Penalized variable selection for cause‐specific hazard frailty models with clustered competing‐risks data

A review of h-likelihood for survival analysis

Deep Learning-Based Residual Control Chart for Binary Response

Deep Learning-Based Survival Analysis for High-Dimensional Survival Data

Penalized variable selection in copula survival models for clustered time-to-event data

Penalized h‐likelihood approach for variable selection in AFT random‐effect models

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