4 papers
Transfer Learning in High-dimensional Ising Models
Joonho Kim, Seyoung Park
In high-dimensional Ising model estimation, target sample sizes are often limited, and effectively using auxiliary binary datasets of unknown relevance remains challenging. To addr…
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
Yeichan Kim, Ilmun Kim, Seyoung Park
Transfer learning is a key component of modern machine learning, enhancing the performance of target tasks by leveraging diverse data sources. Simultaneously, overparameterized mod…
Income Disaster, Role of Income Support, and Optimal Retirement
Tae Ung Gang, Seyoung Park, Yong Hyun Shin
This paper investigates the interactions among consumption/savings, investment, and retirement choices with income disaster. We consider low-income people who are exposed to income…
Kronecker sum covariance models for spatio-temporal data
Shuheng Zhou, Seyoung Park, Kerby Shedden
In this paper, we study the subgaussian matrix variate model, where we observe the matrix variate data which consists of a signal matrix and a noise matrix . More spec…