Orthogonal Principal Coefficients Embedding for Unsupervised Subspace Learning.

As a recently proposed method for subspace learning, principal coefficients embedding (PCE) method can automatically determine the dimension of the feature space and robustly handle various corruptions in real-world applications. However, the projection matrix learned by PCE is not orthogonal, so the original data may be reconstructed improperly. To address this issue, we proposed a new method ter...