Latest version of LMNN (includes non-linear gradient boosted LMNN).
Previous version of LMNN2.4 (outdated)
Maximum Variance Unfolding Matlab Code (original code + landmark version) [Previously called Semidefinite Embedding (SDE)] This code contains the landmark MVU version (AISTATS'05), the Graph Laplacien Regularized version (NIPS'06) and the original MVU code (IJCV'05) (See also http://homepage.tudelft.nl/19j49/Matlab_Toolbox_for_Dimensionality_Reduction.html )
Fast C++ implementation of Gradient Boosted Regression Trees and Random Forests (by Ananth Mohan)
Multi-Task LMNN (NIPS 2010) [Code by Shibin Parameswaran]
High performance parallel implementation (C++/MPI) of gradient boosted regression trees.
marginalized Stacked Denoising Autoencoder (mSDA) [MATLAB, PYTHON]
Re-implementation of Metric learning for kernel regression (MLKR).
Learnign with Marginalized Corrupted Features (Matlab implementation by Laurens van der Maaten).
Co-training for domain adaptation
Pseudo Multi-View Co-Training (PMC)
The Greedy Miser - Gradient Boosted Regression Trees under a cost budget.
Fast Flux Descriminant Features