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» Experiments on Graph Clustering Algorithms
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73
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KDD
2004
ACM
113views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
PAMI
2010
260views more  PAMI 2010»
14 years 8 months ago
Unsupervised Object Segmentation with a Hybrid Graph Model (HGM)
—In this work, we address the problem of performing class-specific unsupervised object segmentation, i.e., automatic segmentation without annotated training images. Object segmen...
Guangcan Liu, Zhouchen Lin, Yong Yu, Xiaoou Tang
DMIN
2007
85views Data Mining» more  DMIN 2007»
14 years 11 months ago
A Clustering Approach for Achieving Data Privacy
Abstract — New privacy regulations together with everincreasing data availability and computational power have created a huge interest in data privacy research. One major researc...
Alina Campan, Traian Marius Truta, John Miller, Ra...
72
Voted
ICASSP
2009
IEEE
15 years 5 months ago
Bandwidth adaptive hardware architecture of K-Means clustering for intelligent video processing
K-Means is a clustering algorithm that is widely applied in many elds, including pattern classi cation and multimedia analysis. Due to real-time requirements and computational-cos...
Tse-Wei Chen, Shao-Yi Chien
ICML
2006
IEEE
15 years 11 months ago
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
The Dirichlet compound multinomial (DCM) distribution, also called the multivariate Polya distribution, is a model for text documents that takes into account burstiness: the fact ...
Charles Elkan