We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of gra...
Clustering performance can often be greatly improved by
leveraging side information. In this paper, we consider constrained
clustering with pairwise constraints, which specify
s...
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...