This repository contains Matlab implementations of the algorithms proposed in "Coupled Dimensionality Reduction and Classification for Supervised and Semi-Supervised Multilabel Learning", which is appearing in Pattern Recognition Letters, and "Bayesian Supervised Multilabel Learning with Coupled Embedding and Classification", which is appearing in the Proceedings of the 12th SIAM International Conference on Data Mining (SDM 2012). demo_supervised.m file shows how to use the algorithm for supervised learning. demo_semisupervised.m file shows how to use the algorithm for semi-supervised learning. BSSML methods ------------- * bssml_supervised_classification_variational_train.m => training procedure for supervised learning * bssml_supervised_classification_variational_test.m => test procedure for supervised learning * bssml_semisupervised_classification_variational_train.m => training procedure for semi-supervised learning * bssml_semisupervised_classification_variational_test.m => test procedure for semi-supervised learning If you use any of the algorithms implemented in this repository, please cite one of the following papers: Mehmet Gonen. Coupled Dimensionality Reduction and Classification for Supervised and Semi-Supervised Multilabel Learning. Pattern Recognition Letters, 38:132-141, 2014. Mehmet Gonen. Bayesian Supervised Multilabel Learning with Coupled Embedding and Classification. Proceedings of the 12th SIAM International Conference on Data Mining (SDM 2012), Anaheim, California, USA, 2012.