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NIPS
2004
15 years 8 months ago
Self-Tuning Spectral Clustering
We study a number of open issues in spectral clustering: (i) Selecting the appropriate scale of analysis, (ii) Handling multi-scale data, (iii) Clustering with irregular backgroun...
Lihi Zelnik-Manor, Pietro Perona
DKE
2006
83views more  DKE 2006»
15 years 6 months ago
Bulk insertion for R-trees by seeded clustering
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach ...
Taewon Lee, Bongki Moon, Sukho Lee
170
Voted
CSDA
2007
99views more  CSDA 2007»
15 years 6 months ago
CLUES: A non-parametric clustering method based on local shrinking
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
Xiaogang Wang, Weiliang Qiu, Ruben H. Zamar
ML
2002
ACM
128views Machine Learning» more  ML 2002»
15 years 6 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
SADM
2008
165views more  SADM 2008»
15 years 6 months ago
Global Correlation Clustering Based on the Hough Transform
: In this article, we propose an efficient and effective method for finding arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set o...
Elke Achtert, Christian Böhm, Jörn David...