The invention includes a method for training a learning machine having a deep multi-layered network, with labeled and unlabeled training data. The deep multi-layered network is a network having multiple layers of non-linear mapping. The method generally includes applying unsupervised embedding to any one or more of the layers of the deep network. The unsupervised embedding is operative as a semi-supervised regularizer in the deep network.