SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
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...
MVA
2007
13 years 6 months ago
2007
We propose a technique to recognize actions of grasshoppers based on spectral clustering. We track the object in 3D and construct features using 3D object movement in segments of ...
NIPS
2008
13 years 6 months ago
2008
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
LREC
2008
13 years 6 months ago
2008
Spectral clustering is a powerful clustering method for document data set. However, spectral clustering needs to solve an eigenvalue problem of the matrix converted from the simil...
LKR
2008
13 years 6 months ago
2008
Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
SDM
2010
SIAM
13 years 6 months ago
2010
SIAM
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...
ECML
2006
Springer
13 years 6 months ago
2006
Springer
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
BIRTHDAY
2010
Springer
13 years 7 months ago
2010
Springer
The present paper analyzes the usefulness of the normalized compression distance for the problem to cluster the hemagglutinin (HA) sequences of influenza virus data for the HA gene...
KDD
2010
ACM
13 years 8 months ago
2010
ACM
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...