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ECCV
2010
Springer
15 years 6 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
NIPS
2004
15 years 5 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 4 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
CSDA
2007
99views more  CSDA 2007»
15 years 4 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 4 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