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SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
15 years 6 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li
JGAA
2007
124views more  JGAA 2007»
14 years 9 months ago
Energy Models for Graph Clustering
The cluster structure of many real-world graphs is of great interest, as the clusters may correspond e.g. to communities in social networks or to cohesive modules in software syst...
Andreas Noack
TIP
2010
97views more  TIP 2010»
14 years 4 months ago
Image Clustering Using Local Discriminant Models and Global Integration
In this paper, we propose a new image clustering algorithm, referred to as Clustering using Local Discriminant Models and Global Integration (LDMGI). To deal with the data points s...
Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yuet...
PAMI
2007
196views more  PAMI 2007»
14 years 9 months ago
Clustering and Embedding Using Commute Times
This paper exploits the properties of the commute time between nodes of a graph for the purposes of clustering and embedding, and explores its applications to image segmentation a...
Huaijun Qiu, Edwin R. Hancock
IBPRIA
2007
Springer
15 years 3 months ago
Motion Segmentation from Feature Trajectories with Missing Data
Abstract. This paper presents a novel approach for motion segmentation from feature trajectories with missing data. It consists of two stages. In the first stage, missing data are...
Carme Julià, Angel Domingo Sappa, Felipe Lu...