MSSS

Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering Publication

Project Description

MSSS

The Nystrom sampling provides an efficient approach for large scale clustering problems, by generating a low-rank matrix approximation. However, existing sampling methods are limited by their accuracies and computing times. Here we propose a scalable Nystrom-based clustering algorithm with a new sampling procedure, called: Minimum Sum of Squared Similarities (MSSS).

Publication

  • Bouneffouf D., Birol I.: Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering.  Proceedings of the Twenty-Fourth international joint conference on Artificial Intelligence (IJCAI) , 2015-July.

Current Release
MSSS 1.0

Released Jun 05, 2015

Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering
More about this release…

Download file Get MSSS for all platforms
MSSSRelease.zip

All Releases

Version Released Description Compatibility Licenses Status
1.0 Jun 05, 2015 Sampling with Minimum Sum of Squared Similarities for Nystrom-Based Large Scale Spectral Clustering More about this release… BCCA (academic use) final
Project Resources

Project owner: Djallel Bouneffouf