When performing dimensionality reduction with linear projections

maximum margin criterion (MMC) is often affected by outliers and noises due to L2-norm.In this paper

L1-norm-based maximum margin criterion (MMC-L1) is proposed for dimensionality reduction.It makes full use of Maximum Margin Criterion and strong robustness of L1-norm to outliers and noises.A rapid iterative optimization algorithm

with its proof of monotonic convergence to local optimum

is given.Experiments on several public image databases verify the robustness and efficiency of the proposed method.