Pre-prints / Submitted Manuscripts
Tian-Yi Zhou, Namjoon Suh, Guang Cheng, Xiaoming Huo. "Approximation of RKHS functionals by neural networks." Submitted to JMLR. [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, Yuning Yang, Din-Yin Hsieh, Qitong Luan, Shirong Xu, Shixiang Zhu, Guang Cheng, "TimeAutoDiff: A unified framework for generation, imputation, forecasting, and time-varying metadata conditioning of heterogeneous time series tabular data" TMLR (2025). [link][github code]
Hyunouk Ko, Namjoon Suh, Xiaoming Huo. "On Excess Risk Convergence Rates of Neural Network Classifiers." IEEE Transactions on Information Theory (2025). [link]
Chaeyun Yeo, Namjoon Suh**, Younghoon Kim, "Fused LassoNet: Sequential Feature Selection for Spectral Data with Neural Networks" Chemometrics and Intelligent Laboratory Systems (2024). [journal link]
Namjoon Suh, Guang Cheng. "A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models " Annual Review of Statistics and Its Application (2024). [journal link][link]
Namjoon Suh, Li-Hsiang Lin, Xiaoming Huo. "High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization." Journal of Computational and Graphical Statistics (2024). [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, ** corresponding author
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][old github code][new 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]