# Tensor Sparse PCA and Face Recognition: A Novel Approach

arXiv: https://arxiv.org/abs/1904.08496 · HTML: https://mlsanity.com/paper/1904.08496/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2019.

## Built on by (most cited first, 2 of 2)

- [Do algorithms and barriers for sparse principal component analysis extend to other structured settings?](https://mlsanity.com/paper/2307.13535/) (2023)
- [Solve sparse PCA problem by employing Hamiltonian system and leapfrog method](https://mlsanity.com/paper/2503.23335/) (2025)

## Abstract (arXiv)

Face recognition is the important field in machine learning and pattern recognition research area. It has a lot of applications in military, finance, public security, to name a few. In this paper, the combination of the tensor sparse PCA with the nearest-neighbor method (and with the kernel ridge regression method) will be proposed and applied to the face dataset. Experimental results show that the combination of the tensor sparse PCA with any classification system does not always reach the best accuracy performance measures. However, the accuracy of the combination of the sparse PCA method and one specific classification system is always better than the accuracy of the combination of the PCA method and one specific classification system and is always better than the accuracy of the classification system itself.