Robust Tensor Analysis with Non-Greedy L1-Norm Maximization
Licheng Zhao, Wenhao Jia, R. Wang, Qiang Yu · Radioengineering · 2016
The ℓ 1 -norm based tensor analysis (TPCA-L1) is recently proposed for dimensionality reduction and feature extraction.However, a greedy strategy was utilized for solving the ℓ 1 -norm maximization problem, which makes it prone to being stuck in local solutions.In this paper, we propose a robust TPCA with non-greedy ℓ 1 -norm maximization (TPCA-L1 non-greedy), in which all projection directions are optimized simultaneously.Experiments on several face databases demonstrate the effectiveness of the proposed method.