Pre-prints / Submitted Manuscripts

• Namjoon Suh, Yuning Yang, Din-Yin Hsieh, Qitong Luan, Shirong Xu, Shixiang Zhu, Guang Cheng,  "TimeAutoDiff: combining Auto-encoder and Diffusion model for time series tabular data synthesizing"  Submitted [link]

• Chaeyun Yeo, Namjoon Suh, Younghoon Kim, "Fused LassoNet: Enhanced feature selection for spectra data in neural networks."  Submitted to Engineering Applications of Artificial Intelligence [In preparation]

• Tian-Yi Zhou, Namjoon Suh, Guang Cheng, Xiaoming Huo. "Approximation of RKHS functionals by neural networks." Submitted to JMLR. [link]

• Hyunouk Ko, Namjoon Suh, Xiaoming Huo. "On Excess Risk Convergence Rates of Neural Network Classifiers." Submitted to IEEE Transactions on Information Theory.  [link]

• Namjoon Suh, Guang Cheng.  "A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models " Invited for review in Annual Review of Statistics and Its Application. [link]

• Yue Xing, Xiaofeng Lin, Namjoon Suh, Qifan Song, Guang Cheng.  "Benefits of Transformer: In-context Learning in Linear Regression Tasks with Unstructured Data." Submitted [link]

Journal Publications

• Namjoon Suh, Li-Hsiang Lin, Xiaoming Huo.  "High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization."  To appear, Journal of Computational and Graphical Statistics. [journal link][link] [supplementary]

• Yuchen He*, Namjoon Suh*, Xiaoming Huo, Sung Ha Kang, Yajun Mei. "Asymptotic theory of L1-regularized PDE identification from single noisy trajectory."  SIAM/ASA Journal on Uncertainty Quantification, Vol 10, Iss. 3 (2022).  [journal link][main paper][supplementary][slide]

• Namjoon Suh, Xiaoming Huo, Eric Heim, Lee Seversky. "A network model that combines latent factors and sparse graphs." Statistical Analysis and Data Mining (2021): 97-115. [journal link][main paper][github code]

 * Joint first authors

Conference Publications (peer-reviewed)

• Namjoon Suh, Xiaofeng Lin, Din-Yin Hsieh, Mehrdad Honarkhah, Guang Cheng.  "AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizing."   Neurips 2023 Workshop SyntheticData4ML.  [workshop link][link] [slide][github code]

• Namjoon Suh, Tian-Yi Zhou, Xiaoming Huo.  "Approximation and non-parametric estimation of functions over high-dimensional sphere via deep ReLU network."  ICLR (2023). [paper link][slide][video]

• Namjoon Suh, Hyunouk Ko, Xiaoming Huo. "A non-parametric regression viewpoint : Generalization of overparametrized deep ReLU network under noisy observations." ICLR (2022). [paper link][slide]

• Namjoon Suh, Ruizhi Zhang, Yajun Mei. "Adaptive online monitoring of Ising model." Allerton (2019). [paper link] 

Technical Report 

• Namjoon Suh.  "Statistical viewpoints on network model, PDE Identification, low-rank matrix estimation and deep learning".  (Nov. 18. 2022).  Ph.D. Thesis [report link]

• Namjoon Suh.  "Non-parametric estimation via neural network".  (2020).  Qualification Exam Report [report link]

• Namjoon Suh.  "Review on parameter estimation of HMRF".  (2017). [report link]