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106
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DATAMINE
2006
157views more  DATAMINE 2006»
15 years 19 days ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
101
Voted
CVPR
2008
IEEE
16 years 2 months ago
Coherent Laplacian 3-D protrusion segmentation
In this paper, an analysis of locally linear embedding (LLE) in the context of clustering is developed. As LLE conserves the local affine coordinates of points, shape protrusions ...
Fabio Cuzzolin, Diana Mateus, David Knossow, Edmon...
TFS
2008
117views more  TFS 2008»
15 years 16 days ago
A New Fuzzy Set Merging Technique Using Inclusion-Based Fuzzy Clustering
Abstract--This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzz...
Samia Nefti, Mourad Oussalah, Uzay Kaymak
TKDE
2008
148views more  TKDE 2008»
15 years 15 days ago
Semisupervised Clustering with Metric Learning using Relative Comparisons
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also...
Nimit Kumar, Krishna Kummamuru
85
Voted
UAI
2008
15 years 2 months ago
Learning and Solving Many-Player Games through a Cluster-Based Representation
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...
Sevan G. Ficici, David C. Parkes, Avi Pfeffer