• Huang, S.-C. and Tsay, R. S. (2024) Scalable High-dimensional Multivariate Linear Regression for Feature-distributed Data. Journal of Machine Learning Research. [Codes]

• Huang, S.-C. and Tsay, R. S. (2024) Time Series Forecasting with Many Predictors. Mathematics. 

• Huang, S.-C., Ing, C.-K., and Tsay, R. S. (2026) Model Selection for Unit-root Time Series with Many Predictors. Electronic Journal of Statistics. [Codes] 

• Huang, S.-C., Liang, T., and Tsay, R. S. Missing Values in Time Series: A Brief Review and a New Versatile Imputation Method. Submitted. [Codes]

  • Previously circulated as "Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation."

• Huang, S.-C., Chen, Y., and Chen, R. A Riemannian Factor Model for Manifold-valued Time Series. Submitted.

• Huang, S.-C., Chi, C.-M., and Chen, J.-E. Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions. Submitted.

Reviews

• Bolivar S., Huang, S.-C., and Chen, R. (2025) Analysis of Tensor Time Series. Annual Review of Statistics and Its Applications. [Paper][Resource Website]

• Inference for Structural Breaks for Time Series on Manifolds (with Rong Chen and Yaqing Chen)

• Post Empirical Bayes Regression (with Sheng-Kai Chang, Yu-Chang Chen, and Shen-Hsun Liao)

• Provable Tensor-on-tensor Regression with Low CP Rank (with Cun-Hui Zhang)