2 papers
stat.ME2024
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, probabil…
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…