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

Huang, S.-C. and Tsay, R. S. (2024) Time Series Forecasting with Many Predictors. Mathematics. [Paper][Preprint]

Huang, S.-C., Ing, C.-K., and Tsay, R. S. Model Selection for Unit-root Time Series with Many Predictors. Submitted. [Preprint][Codes] 

• Presentation: Joint Statistical Meetings 2024, Portland; NBER-NSF Time Series 2022, Boston (Plenary session)

Huang, S.-C., Liang, T., and Tsay, R. S. Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation. Submitted. [Preprint][Codes]

• Presentation: SLDS 2024, Los Angeles; Joint Statistical Meetings 2025, Nashville

Bolivar S., Huang, S.-C., and Chen, R. Analysis of Tensor Time Series. Forthcoming in Annual Review of Statistics and Its Applications. [Resource Website]

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)

Riemannian factor model: Dimension reduction for manifold-valued time series (with Rong Chen and Yaqing Chen)

On the inference of trends for spherical time series (with Rong Chen and Yaqing Chen)