LKR
2008
13 years 7 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...
ECCV
2010
Springer
13 years 8 months ago
2010
Springer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Spectral clustering has attracted much research interest in recent years since it can yield impressively good clustering results. Traditional spectral clustering algorithms first s...
ICRA
2007
IEEE
14 years 2 days ago
2007
IEEE
Abstract— This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is increm...
KDD
2005
ACM
14 years 6 months ago
2005
ACM
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
ECCV
2004
Springer
14 years 7 months ago
2004
Springer
Abstract. This paper addresses the problem of clustering images of objects seen from different viewpoints. That is, given an unlabelled set of images of n objects, we seek an unsup...
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
This paper aims to introduce the robustness against noise into the spectral clustering algorithm. First, we propose a warping model to map the data into a new space on the basis o...