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PRL
2008
135views more  PRL 2008»
13 years 7 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
CVPR
2006
IEEE
14 years 9 months ago
Spectral Methods for Automatic Multiscale Data Clustering
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
Arik Azran, Zoubin Ghahramani
ECAI
2010
Springer
13 years 8 months ago
A Very Fast Method for Clustering Big Text Datasets
Large-scale text datasets have long eluded a family of particularly elegant and effective clustering methods that exploits the power of pair-wise similarities between data points ...
Frank Lin, William W. Cohen
ICML
2010
IEEE
13 years 8 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...
RIAO
2007
13 years 8 months ago
Similarity Beyond Distance Measurement
One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and mos...
Feng Kang, Rong Jin, Steven C. H. Hoi