bellet / HDSL

High-Dimensional Similarity Learning

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.

Getting started

To install and run a demo, please use inside the Matlab console

install
demo_HDSL

References

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.