About the code

This is the code for the paper

Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu. Fast Low-rank Metric Learning for Large-scale and High-dimensional Data. NeurIPS 2019.

Run the code

1. do_SVD.m

Run the SVD preprocessing.

2. train_FLRML.m

Run FLRML.

3. train_MFLRML.m

Run Minibatch-FLRML.

4. test.m

Run KNN test.

Tools included in the code

./tools/FOptM-share/

Available from: https://github.com/wenstone/OptM

Reference: Wen, Z. and Yin, W. A feasible method for optimization with orthogonality constraints. Mathematical Programming, 142(1-2):397–434, 2013.

./tools/beta_pca/

Available from: http://tygert.com/beta.tar.gz

Reference: Li, H., Linderman, G., Szlam, A., Stanton, K., Kluger, Y., and Tygert, M. Algorithm 971: An implementation of a randomized algorithm for principal component analysis. ACM Transactions on Mathematical Software, 43(3):28:1–28:14, 2017. ISSN 0098-3500.