We proposed a newly semi-supervised manifold learning algorithm named Discriminative Sparse Manifold Regularization (DSMR) to classify.

For each labeled or unlabeled sample, its dictionary is updated according to its property and use the new dictionary to reconstruct it.

Extensive experiments on the several UCI data sets and face data sets demonstrate the effectiveness of the proposed DSMR.