Tight Local Intrinsic Dimensionality Estimator (TLE)

Laurent Amsaleg, Oussama Chelly, Michael E. Houle, Ken-ichi Kawarabayashi, Miloš Radovanović and Weeris Treeratanajaru

This page has been superseded by a new version on GitHub, please visit https://github.com/radacha/tle.

Welcome to the support page for the Tight Local intrinsic dimensionality Estimator (TLE) described in the paper:

Laurent Amsaleg, Oussama Chelly, Michael E. Houle, Ken-ichi Kawarabayashi, Miloš Radovanović and Weeris Treeratanajaru. Intrinsic dimensionality estimation within tight localities. In Proceedings of the SIAM International Conference on Data Mining (SDM), pages 181–189, Calgary, Alberta, Canada, 2019 [pdf]

and the accompanying supplement [pdf].

Downloads:

Matlab code implementing intrinsic dimensionality (ID) estimators and experiments described in the paper is available here.

Real data sets are available here (~490MB).

Synthetic data sets from the "m-family" are available here (~120MB).

Licensing information:

The released code is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License: http://creativecommons.org/licenses/by-sa/4.0/

For attribution, please cite the above paper.