Locally Linear Embedding by Linear Programming

Abstract Dimensionality reduction has always been one of the most challenging tasks in the field of data mining. As a nonlinear dimensionality reduction method, locally linear embedding (LLE) has drawn more and more attention and applied widely in face image processing and text data processing. But this method is usually sensitive to noise, which limits its application in many fields. In this paper, we propose a locally linear embedding algorithm by linear programming (LLE by LP), and the experiments demonstrate the effectiveness of the approach in reducing the sensitivity to noise.