7 citations · 13 across the 5 of their papers we have counts for
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stat.ML2018
Robust Sparse Reduced Rank Regression in High Dimensions
Kean Ming Tan, Qiang Sun, Daniela Witten
We propose robust sparse reduced rank regression for analyzing large and complex high-dimensional data with heavy-tailed random noise. The proposed method is based on a convex rela…
stat.ML2018
A convex formulation for high-dimensional sparse sliced inverse regression
Kean Ming Tan, Zhaoran Wang, Tong Zhang +2
Sliced inverse regression is a popular tool for sufficient dimension reduction, which replaces covariates with a minimal set of their linear combinations without loss of informatio…