8 citations · 12 across the 6 of their papers we have counts for
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stat.ME2024★ 1 cited
Fréchet Sufficient Dimension Reduction for Metric Space-Valued Data via Distance Covariance
Hsin-Hsiung Huang, Feng Yu, Kang Li +1
We propose a novel Fréchet sufficient dimension reduction (SDR) method based on kernel distance covariance, tailored for metric space-valued responses such as count data, probabili…
cs.CV2024
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion
Feng Yu, Teng Zhang, Gilad Lerman
We present the subspace-constrained Tyler's estimator (STE) designed for recovering a low-dimensional subspace within a dataset that may be highly corrupted with outliers. STE is a…
stat.ME2024★ 2 cited
Robust Sufficient Dimension Reduction via -Distance Covariance
Hsin-Hsiung Huang, Feng Yu, Teng Zhang
We introduce a novel sufficient dimension-reduction (SDR) method which is robust against outliers using -distance covariance (dCov) in dimension-reduction problems. Under very m…