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» Minimization and Partitioning Method Reducing Input Sets
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CVPR
2008
IEEE
16 years 3 months ago
Computing minimal deformations: application to construction of statistical shape models
Nonlinear registration is mostly performed after initialization by a global, linear transformation (in this work, we focus on similarity transformations), computed by a linear reg...
Darko Zikic, Michael Sass Hansen, Ben Glocker, Ali...
CSDA
2007
99views more  CSDA 2007»
15 years 1 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
KER
2006
107views more  KER 2006»
15 years 1 months ago
Partitioning strategies for distributed association rule mining
In this paper a number of alternative strategies for distributed/parallel association rule mining are investigated. The methods examined make use of a data structure, the T-tree, ...
Frans Coenen, Paul H. Leng
CONCUR
2001
Springer
15 years 6 months ago
Compositional Methods for Probabilistic Systems
Abstract. We present a compositional trace-based model for probabilistic systems. The behavior of a system with probabilistic choice is a stochasticprocess, namely, a probability d...
Luca de Alfaro, Thomas A. Henzinger, Ranjit Jhala
DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
15 years 5 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu