4 papers
Scale-Invariant Robust Estimation of High-Dimensional Kronecker-Structured Matrices
Xiaoyu Zhang, Zhiyun Fan, Wenyang Zhang +1
High-dimensional Kronecker-structured estimation faces a conflict between non-convex scaling ambiguities and statistical robustness. The arbitrary factor scaling distorts gradient…
High-dimensional low-rank matrix regression with unknown latent structures
Di Wang, Xiaoyu Zhang, Guodong Li +1
We study low-rank matrix regression in settings where matrix-valued predictors and scalar responses are observed across multiple individuals. Rather than assuming a fully homogeneo…
A Hybrid Framework Combining Autoregression and Common Factors for Matrix Time Series
Zhiyun Fan, Xiaoyu Zhang, Di Wang
Matrix-valued time series are ubiquitous in modern economics and finance, yet modeling them requires navigating a trade-off between flexibility and parsimony. We propose the Matrix…
Robust Gradient Descent Estimation for Tensor Models under Heavy-Tailed Distributions
Xiaoyu Zhang, Di Wang, Guodong Li +1
Low-rank tensor models are widely used in statistics. However, most existing methods rely heavily on the assumption that data follows a sub-Gaussian distribution. To address the ch…