Regularizing multiple kernel learning using response surface methodology

DOI10.1016/j.patcog.2010.07.008zbMath1207.68279OpenAlexW2117924446WikidataQ62654696 ScholiaQ62654696MaRDI QIDQ609194

Ethem Alpaydın, Mehmet Gönen

Publication date: 30 November 2010

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.07.008

zbMATH Keywords

regularizationsupport vector machineresponse surface methodologymultiple kernel learning

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (2)

Improving localized multiple kernel learning via radius-margin bound ⋮ Structural multiple empirical kernel learning

Uses Software

• SHOGUN
• Mosek

Cites Work

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• Support vector machines with applications
• Feature space perspectives for learning the kernel
• 10.1162/153244302760200687
• Structural, Syntactic, and Statistical Pattern Recognition
• Choosing multiple parameters for support vector machines

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