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JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
TOG
2008
193views more  TOG 2008»
13 years 9 months ago
Random-access rendering of general vector graphics
We introduce a novel representation for random-access rendering of antialiased vector graphics on the GPU, along with efficient encoding and rendering algorithms. The representati...
Diego Nehab, Hugues Hoppe
ICPR
2006
IEEE
14 years 10 months ago
Machine Learning for Video Compression: Macroblock Mode Decision
Video Compression currently is dominated by engineering and fine-tuned heuristic methods. In this paper, we propose to instead apply the well-developed machinery of machine learni...
Christoph H. Lampert
QSIC
2008
IEEE
14 years 3 months ago
Using Machine Learning to Refine Black-Box Test Specifications and Test Suites
In the context of open source development or software evolution, developers are often faced with test suites which have been developed with no apparent rationale and which may nee...
Lionel C. Briand, Yvan Labiche, Zaheer Bawar
ESANN
2004
13 years 10 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...