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Simple Solvers for Large Quadratic Programming Tasks

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Pattern Recognition (DAGM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3663))

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Abstract

This paper describes solvers for specific quadratic programming (QP) tasks. The QP tasks in question appear in numerous problems, e.g., classifier learning and probability density estimation. The QP task becomes challenging when large number of variables is to be optimized. This the case common in practice. We propose QP solvers which are simple to implement and still able to cope with problems having hundred thousands variables.

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© 2005 Springer-Verlag Berlin Heidelberg

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Franc, V., Hlaváč, V. (2005). Simple Solvers for Large Quadratic Programming Tasks. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_10

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  • DOI: https://doi.org/10.1007/11550518_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28703-2

  • Online ISBN: 978-3-540-31942-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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