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Fast adaptive PARAFAC decomposition algorithm with linear complexity

Abstract : We present a fast adaptive PARAFAC decomposition algorithm with low computational complexity. The proposed algorithm generalizes the Orthonormal Projection Approximation Subspace Tracking (OPAST) approach for tracking a class of third-order tensors which have one dimension grow- ing with time. It has linear complexity, good convergence rate and good estimation accuracy. To deal with large-scale problems, a parallel implementation can be applied to reduce both computational complexity and storage. We illustrate the effectiveness of our algorithm in comparison with the state-of-the-art algorithms through simulation experiments.
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https://hal.inria.fr/hal-01306461
Contributor : Viet-Dung Nguyen <>
Submitted on : Friday, August 5, 2016 - 10:32:02 AM
Last modification on : Monday, July 16, 2018 - 4:00:45 PM

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Viet-Dung Nguyen, Karim Abed-Meraim, Linh-Trung Nguyen. Fast adaptive PARAFAC decomposition algorithm with linear complexity. International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Mar 2016, Shanghai, China. ⟨hal-01306461⟩

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