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ICML
2010
IEEE
13 years 6 months ago
The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
IPPS
2003
IEEE
13 years 11 months ago
Natural Block Data Decomposition for Heterogeneous Clusters
We propose general purposes natural heuristics for static block and block-cyclic heterogeneous data decomposition over processes of parallel program mapped into multidimensional g...
Egor Dovolnov, Alexey Kalinov, Sergey Klimov
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICDM
2010
IEEE
232views Data Mining» more  ICDM 2010»
13 years 3 months ago
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration
Community detection is an important task for mining the structure and function of complex networks. Many pervious approaches are difficult to detect communities with arbitrary size...
Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, ...
CVPR
2007
IEEE
14 years 7 months ago
Adaptive Distance Metric Learning for Clustering
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
Jieping Ye, Zheng Zhao, Huan Liu