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ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
15 years 4 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
CORR
2010
Springer
179views Education» more  CORR 2010»
14 years 6 months ago
The DMM bound: multivariate (aggregate) separation bounds
In this paper we derive aggregate separation bounds, named after Davenport-MahlerMignotte (DMM), on the isolated roots of polynomial systems, specifically on the minimum distance ...
Ioannis Z. Emiris, Bernard Mourrain, Elias P. Tsig...
86
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ECCV
2008
Springer
15 years 11 months ago
Anisotropic Geodesics for Perceptual Grouping and Domain Meshing
This paper shows how computational Riemannian manifold can be used to solve several problems in computer vision and graphics. Indeed, Voronoi segmentations and Delaunay graphs comp...
Sébastien Bougleux, Gabriel Peyré, L...
APWEB
2005
Springer
15 years 3 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...
JMLR
2010
129views more  JMLR 2010»
14 years 4 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert