The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
In this paper we formulate spectral clustering in directed graphs as an optimization problem, the objective being a weighted cut in the directed graph. This objective extends seve...
We present a generalized version of spectral clustering using the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian. We show that the second eigenvecto...
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...