%0 Conference Paper
%A Le, Trung Thanh
%A Karim, Abed Meraim
%A Nguyen, Linh Trung
%A Adel, Hafiane
%B ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
%C Canada
%D 2021
%F SisLab:4453
%P 2910-2914
%T A Fast Randomized Adaptive CP Decomposition For Streaming Tensors
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4453/
%X In this paper, we introduce a fast adaptive algorithm for CAN- DECOMP/PARAFAC decomposition of streaming three-way tensors using randomized sketching techniques. By leveraging randomized least-squares regression and approximating matrix multiplication, we propose an efficient first-order estimator to minimize an exponentially weighted recursive least- squares cost function. Our algorithm is fast, requiring a low computational complexity and memory storage. Experiments indicate that the proposed algorithm is capable of adaptive tensor decomposition with a competitive performance evaluation on both synthetic and real data.