Learning low-dimensional nonlinear structures from high-dimensional noisy data: An integral operator approach
Work
Year: 2023
Type: article
Abstract: We propose a kernel-spectral embedding algorithm for learning low-dimensional nonlinear structures from noisy and high-dimensional observations, where the data sets are assumed to be sampled from a no... more
Source: The Annals of Statistics
Authors Xiucai Ding, Rong Ma
Institutions University of California, Davis, Stanford University
Cites: 54
Cited by: 2
Related to: 10
FWCI: 0.565
Citation percentile (by year/subfield): 40.04
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green