2 citations · 2 across the 4 of their papers we have counts for
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Optimal Sparse Sliced Inverse Regression via Random Projection
Jia Zhang, Runxiong Wu, Xin Chen
We propose a novel sparse sliced inverse regression method based on random projections in a large small setting. Embedded in a generalized eigenvalue framework, the propose…
High-Dimensional Sparse Single-Index Regression Via Hilbert-Schmidt Independence Criterion
Runxiong Wu, Chang Deng, Xin Chen
Hilbert-Schmidt Independence Criterion (HSIC) has recently been used in the field of single-index models to estimate the directions. Compared with some other well-established metho…
Sufficient Dimension Reduction for Classification
Xin Chen, Jingjing Wu, Zhigang Yao +1
We propose a new sufficient dimension reduction approach designed deliberately for high-dimensional classification. This novel method is named maximal mean variance (MMV), inspired…
High Dimensional Elliptical Sliced Inverse Regression in non-Gaussian Distributions
Jia Zhang, Xin Chen, Wang Zhou
Sliced inverse regression (SIR) is the most widely-used sufficient dimension reduction method due to its simplicity, generality and computational efficiency. However, when the dist…