Robust Subspace Tracking With Contamination Mitigation via α-Divergence
Abstract: We studied the problem of robust subspace tracking (RST) in contaminated environments. Leveraging the fast approximated power iteration and α-divergence, a novel robust algorithm called αFAPI was developed for tracking the underlying principal subspace of streaming data over time. αFAPI is fast and it outperforms many RST methods while only having a low complexity linear to the data dimension. Some experiments were conducted to illustrate the performance of αFAPI.
Matlab Code: https://github.com/thanhtbt/aFAPI
Comment: Accepted at IEEE ICASSP 2023
Email Address of Submitting Authortrungfirstname.lastname@example.org
Submitting Author's InstitutionUniversity of Orleans
Submitting Author's Country