| Paper ID | MLSP-7.2 |
| Paper Title |
A FAST RANDOMIZED ADAPTIVE CP DECOMPOSITION FOR STREAMING TENSORS |
| Authors |
Trung Thanh Le, Karim Abed-Meraim, University of Orleans, France; Linh Trung Nguyen, VNU University of Engineering and Technology, Vietnam; Adel Hafiane, INSA Centre Val de Loire, France |
| Session | MLSP-7: Tensor Signal Processing |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 14:00 - 14:45 |
| Presentation Time: | Tuesday, 08 June, 14:00 - 14:45 |
| Presentation |
Poster
|
| Topic |
Machine Learning for Signal Processing: [MLR-TNSR] Tensor-based signal processing |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
In this paper, we introduce a fast adaptive algorithm for CANDECOMP/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. |
