Supervised Low-Rank Embedded Regression (SLRER) for Robust Subspace Learning

Locality-preserving projection (LPP) has been widely used in feature extraction. However, LPP does not use data category information and uses the ${L}_{2}$ -norm for distance measurement, which is highly sensitive to outliers. In this paper, we consider the LPP weight matrix from a supervised perspective and combine the low-ra...