Fast k-means software

This page is for research in accelerating the k-means clustering algorithm. This is for the following papers:

1. Petr Ryšavý, Greg Hamerly. Geometric methods to accelerate k-means algorithms To appear at SDM 2016, 2016. [pdf, supplementary graphs]
2. Greg Hamerly, Jonathan Drake. Accelerating Lloyd's algorithm for k-means clustering. Chapter in Partitional Clustering Algorithms (Springer), 2014. [pdf]
3. Jonathan Drake, Greg Hamerly. Accelerated k-means with adaptive distance bounds. In OPT2012: the 5th NIPS Workshop on Optimization for Machine Learning, December, 2012. [pdf]
4. Greg Hamerly, Making k-means even faster In proceedings of the 2010 SIAM international conference on data mining (SDM 2010), April 2010. [pdf]

Presentations

• Invited talk: Towards the world's fastest k-means algorithm, presented at Sandia Labs, May 15 2014.

Software

• Fast k-means toolkit (Version 0.1, released May 17 2014)

Datasets

• SDM 2010 paper datasets (contains 7 datasets, roughly 147 MB download)

Copyright © 2014 Greg Hamerly
Computer Science Department
Baylor University

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