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TNN
2010
155views Management» more  TNN 2010»
15 years 25 days ago
Incorporating the loss function into discriminative clustering of structured outputs
Clustering using the Hilbert Schmidt independence criterion (CLUHSIC) is a recent clustering algorithm that maximizes the dependence between cluster labels and data observations ac...
Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. ...
ICDM
2010
IEEE
216views Data Mining» more  ICDM 2010»
15 years 4 months ago
K-AP: Generating Specified K Clusters by Efficient Affinity Propagation
Abstract--The Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007) provides an understandable, nearly optimal summary of a data set. However, it suffers...
Xiangliang Zhang, Wei Wang, Kjetil Nørv&ari...
147
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SIGARCH
2010
91views more  SIGARCH 2010»
15 years 26 days ago
Programming framework for clusters with heterogeneous accelerators
We describe a programming framework for high performance clusters with various hardware accelerators. In this framework, users can utilize the available heterogeneous resources pr...
Kuen Hung Tsoi, Anson H. T. Tse, Peter Pietzuch, W...
ANNPR
2010
Springer
16 years 29 days ago
Cluster Analysis of Cortical Pyramidal Neurons Using SOM
Abstract. A cluster analysis using SOM has been performed on morphological data derived from pyramidal neurons of the somatosensory cortex of normal and transgenic mice.
Andreas Schierwagen, Thomas Villmann, Alán ...
CGF
2010
171views more  CGF 2010»
15 years 2 months ago
Efficient Mean-shift Clustering Using Gaussian KD-Tree
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
Chunxia Xiao, Meng Liu