High-Dimensional Similarity Learning
HDSL is a Matlab/MEX implementation of the similarity learning method introduced in our AISTATS 2015 (see also the longer journal version). HDSL allows scalable learning of sparse bilinear similarity functions on high-dimensional data.
HDSL is distributed under GNU/GPL 3 license.
To install and run a demo, please use inside the Matlab console
If you use this code in scientific work, please cite:
K. Liu, A. Bellet and F. Sha. Similarity Learning for High-Dimensional Sparse Data. International Conference on Artificial Intelligence and Statistics (AISTATS), 2015.
K. Liu and A. Bellet. Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds. Neurocomputing 333:185-199, 2019.