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183
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JC
2008
96views more  JC 2008»
15 years 6 months ago
Adaptivity and computational complexity in the numerical solution of ODEs
In this paper we analyze the problem of adaptivity for one-step numerical methods for solving ODEs, both IVPs and BVPs, with a view to generating grids of minimal computational co...
Silvana Ilie, Gustaf Söderlind, Robert M. Cor...
JMLR
2006
89views more  JMLR 2006»
15 years 6 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
GEOINFORMATICA
2002
84views more  GEOINFORMATICA 2002»
15 years 6 months ago
Simultaneous Graphic Generalization of Vector Data Sets
Manual cartographic generalization is a simultaneous process. However, most automatic approaches so far have been sequential; generalization operators are applied one at a time in...
Lars Harrie, Tapani Sarjakoski
186
Voted
ICPR
2010
IEEE
15 years 4 months ago
Learning the Kernel Combination for Object Categorization
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
Deyuan Zhang, Xiaolong Wang, Bingquan Liu
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
15 years 4 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang