Robust Subspace Tracking with Contamination Mitigation via α-Divergence
AM Rekavandi, AK Seghouane… - ICASSP 2023-2023 …, 2023 - ieeexplore.ieee.org
AM Rekavandi, AK Seghouane, K Abed-Meraim
ICASSP 2023-2023 IEEE International Conference on Acoustics …, 2023•ieeexplore.ieee.orgWe 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.
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.
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.
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