From the 2 of 4 linked papers with an AI index.
4 papers
A Riemannian Factor Model for Manifold-Valued Time Series
Shuo-Chieh Huang, Rong Chen, Yaqing Chen
The paper introduces a Riemannian factor model for analyzing high-dimensional time series that reside on Riemannian manifolds, provides dimension‑free convergence rates for the est…
Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions
Shuo-Chieh Huang, Chien-Ming Chi, Jau-er Chen
The paper introduces BAND, a sparse Bayesian network method for high‑dimensional distribution estimation that achieves faster polynomial convergence rates by leveraging sparsity-aw…
Model Selection for Unit-root Time Series with Many Predictors
Shuo-Chieh Huang, Ching-Kang Ing, Ruey S. Tsay
This paper studies model selection for general unit-root time series, including the case with many exogenous predictors. We propose a new model selection algorithm, FHTD, that leve…
Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation
Shuo-Chieh Huang, Tengyuan Liang, Ruey S. Tsay
Missing data can significantly hamper standard time series analysis, yet they occur frequently in applications. In this paper, we introduce temporal Wasserstein imputation, a novel…