3 citations · 5 across the 3 of their papers we have counts for
4 papers
Fréchet Sufficient Dimension Reduction for Random Objects
Chao Ying, Zhou Yu
We in this paper consider Fréchet sufficient dimension reduction with responses being complex random objects in a metric space and high dimension Euclidean predictors. We propose a…
Distributed estimation of principal support vector machines for sufficient dimension reduction
Jun Jin, Chao Ying, Zhou Yu
The principal support vector machines method (Li et al., 2011) is a powerful tool for sufficient dimension reduction that replaces original predictors with their low-dimensional li…
Dynamic Partial Sufficient Dimension Reduction
Lu Li, Kai Tan, Xuerong Meggie Wen +1
Sufficient dimension reduction aims for reduction of dimensionality of a regression without loss of information by replacing the original predictor with its lower-dimensional subsp…
Overlapping Sliced Inverse Regression for Dimension Reduction
Ning Zhang, Zhou Yu, Qiang Wu
Sliced inverse regression (SIR) is a pioneer tool for supervised dimension reduction. It identifies the effective dimension reduction space, the subspace of significant factors wit…