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» A Tutorial on Spectral Clustering
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141
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ICML
2005
IEEE
16 years 3 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
94
Voted
NIPS
2003
15 years 4 months ago
Pairwise Clustering and Graphical Models
Significant progress in clustering has been achieved by algorithms that are based on pairwise affinities between the datapoints. In particular, spectral clustering methods have ...
Noam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss
87
Voted
KDD
2004
ACM
136views Data Mining» more  KDD 2004»
16 years 3 months ago
Exploring the community structure of newsgroups
d Abstract] Christian Borgs Jennifer Chayes Mohammad Mahdian Amin Saberi We propose to use the community structure of Usenet for organizing and retrieving the information stored i...
Christian Borgs, Jennifer T. Chayes, Mohammad Mahd...
111
Voted
ICCV
2005
IEEE
15 years 8 months ago
A Unifying Approach to Hard and Probabilistic Clustering
We derive the clustering problem from first principles showing that the goal of achieving a probabilistic, or ”hard”, multi class clustering result is equivalent to the algeb...
Ron Zass, Amnon Shashua
116
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IGARSS
2010
15 years 20 days ago
Spatial preprocessing for endmember extraction using unsupervised clustering and orthogonal subspace projection concepts
In this paper, we develop a new spatial preprocessing strategy which can be applied prior to a spectral-based endmember extraction process for unmixing of hyperspectral data. Our ...
Gabriel Martin, Antonio J. Plaza