8 citations · 23 across the 8 of their papers we have counts for
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stat.ML2019
Low-Rank Principal Eigenmatrix Analysis
Krishna Balasubramanian, Elynn Y. Chen, Jianqing Fan +1
Sparse PCA is a widely used technique for high-dimensional data analysis. In this paper, we propose a new method called low-rank principal eigenmatrix analysis. Different from spar…
stat.ME2019★ 8 cited
Helping Effects Against Curse of Dimensionality in Threshold Factor Models for Matrix Time Series
Xialu Liu, Elynn Chen
As is known, factor analysis is a popular method to reduce dimension for high-dimensional data. For matrix data, the dimension reduction can be more effectively achieved through bo…
econ.EM2019
Modeling Dynamic Transport Network with Matrix Factor Models: with an Application to International Trade Flow
Elynn Y. Chen, Rong Chen
International trade research plays an important role to inform trade policy and shed light on wider issues relating to poverty, development, migration, productivity, and economy. W…