| 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 | ||
| 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. | ||