Work in Progress
Oh-Ran Kwon, Gourab Mukherjee, and Jacob Bien. Semi-supervised Learning of Noisy Mixture of Experts.
Oh-Ran Kwon, Elizabeth C. Atwood, Bror Jönsson, Thomas Jackson, and Jacob Bien. A Statistical Viewpoint on Predicting Ocean Chlorophyll from Satellites.
Tate Jacobson and Oh-Ran Kwon. Envelope-guided Regularization in High-dimensional Regression.
Preprints
GyeongTaek Lee and Oh-Ran Kwon (2024) A Predictive Model Based on Transformer with Statistical Feature Embedding in Manufacturing Sensor Dataset. [pdf]
Publications
Oh-Ran Kwon and Hui Zou (2024) Enhanced Response Envelope via Envelope Regularization, Journal of the American Statistical Association, 1-22. DOI: 10.1080/01621459.2024.2368844 [software] [code for paper examples]
Oh-Ran Kwon, Zhaosong Lu, and Hui Zou (2024) Exactly Uncorrelated Sparse Principal Component Analysis, Journal of Computational and Graphical Statistics, 33(1), 231-241. DOI: 10.1080/10618600.2023.2232843 [software]
Oh-Ran Kwon and Hui Zou (2023) Leaky Hockey Stick Loss: The First Negatively Divergent Margin-based Loss Function for Classification, Journal of Machine Learning Research, 24(239), 1-40. URL: http://jmlr.org/papers/v24/22-1104.html [software]
Ho Il Yoon, Oh-Ran Kwon, et al. (2016) Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer, Journal of Cancer Prevention, 21(3), 187-193. DOI: 10.15430/JCP.2016.21.3.187