Improving localized multiple kernel learning via radius-margin bound

DOI10.1155/2017/4579214zbMath1426.68242OpenAlexW2570832236WikidataQ59147557 ScholiaQ59147557MaRDI QIDQ1992765

Yanyan Li

Publication date: 5 November 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/4579214

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• SHOGUN
• UCI-ml
• SimpleMKL

Cites Work

• Structural multiple empirical kernel learning
• Regularizing multiple kernel learning using response surface methodology
• Localized algorithms for multiple kernel learning
• Radius Margin Bounds for Support Vector Machines with the RBF Kernel
• Choosing multiple parameters for support vector machines
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