4 citations · 10 across the 9 of their papers we have counts for
15 papers · 1 filter
Robust Statistical Inference for Large-dimensional Matrix-valued Time Series via Iterative Huber Regression
Yong He, Xin-Bing Kong, Dong Liu +1
Matrix factor model is drawing growing attention for simultaneous two-way dimension reduction of well-structured matrix-valued observations. This paper focuses on robust statistica…
Simultaneous Estimation and Dataset Selection for Transfer Learning in High Dimensions by a Non-convex Penalty
Zeyu Li, Dong Liu, Yong He +1
In this paper, we propose to estimate model parameters and identify informative source datasets simultaneously for high-dimensional transfer learning problems with the aid of a non…
Huber Principal Component Analysis for Large-dimensional Factor Models
Yong He, Lingxiao Li, Dong Liu +1
Factor models have been widely used in economics and finance. However, the heavy-tailed nature of macroeconomic and financial data is often neglected in the existing literature. To…
Robust Tensor Factor Analysis
Matteo Barigozzi, Yong He, Lingxiao Li +1
We consider (robust) inference in the context of a factor model for tensor-valued sequences. We study the consistency of the estimated common factors and loadings space when using…
Manifold Principle Component Analysis for Large-Dimensional Matrix Elliptical Factor Model
ZeYu Li, Yong He, Xinbing Kong +1
Matrix factor model has been growing popular in scientific fields such as econometrics, which serves as a two-way dimension reduction tool for matrix sequences. In this article, we…
Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data
Dong Liu, Changwei Zhao, Yong He +3
Graphical models play an important role in neuroscience studies, particularly in brain connectivity analysis. Typically, observations/samples are from several heterogenous groups a…