@inproceedings{kumar2013spectral,
author = {Kumar, Peeyush and L, Niveditha and Ravindran, Balaraman},
title = {Spectral clustering as mapping to a simplex},
booktitle = {ICML workshop on Spectral Learning},
year = {2013},
month = {December},
abstract = {Spectral methods have been widely used to study the structural properties of unlabeled datasets. In this work we describe a clustering approach that exploits the structural properties in the configuration space of objects as well as the spectral sub-space, quite unlike earlier methods. We propose a spectral clustering approach, where we formalize the notion of clusters as vertices of a simplex in the spectral subspace. We define clustering as memberships of data points to vertices of this simplex. We empirically demonstrate that our method is comparable to the state-of-theart methods in a variety of domains and outperforms other generic clustering algorithms},
url = {http://approjects.co.za/?big=en-us/research/publication/spectral-clustering-as-mapping-to-a-simplex/},
}