Error Bounds for lp-Norm Multiple Kernel Learning with Least Square Loss
The problem of learning the kernel function with linear combinations of multiple kernels has attracted considerable attention recently in machine learning. Specially, by imposing an lp-norm penalty on the kernel combination coefficient, multiple kernel learning (MKL) was proved useful and effective...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2012/915920 |
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