Spectral Clustering

Over the past few years, Spectral Clustering has become one of the more popular clustering algorithms. There are several known implementations to the method and therein lies the reason for its popularity: simple to implement, efficient to compute, and outperforms traditional clustering algorithms such as k-means.

Here are some great papers on the matter:

1. Ulrike von Luxburg (2007). A tutorial on spectral clustering. Statistics and Computing, 17(4), pages 395-416, December 2007. [Springer]
2. Andrew Y. Ng, Michael I. Jordan, Yair Weiss (2002). On spectral clustering: Analysis and an algorithm. In Proceedings of Advances in Neural Information Processing Systems 14, Vancouver, Canada, December 2001. [CiteSeerX]
3. Yair Weiss (1999). Segmentation using eigenvectors: A unifying view. In International Conference on Computer Vision, 1999. [PDF]