📄 Conference Paper
SPF-GMKL
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Abstract
Multiple Kernel Learning (MKL) aims to learn the kernel in an SVM from training data. Many MKL formulations have been proposed and some have proved effective in certain applications. Nevertheless, as MKL is a nascent field, many more formulations need to be developed to generalize across domains and meet the challenges of real world applications. However, each MKL formulation typically necessitates the development of a specialized optimization algorithm. The lack of an efficient, general purpose optimizer capable of handling a wide range of formulations presents a significant challenge to those looking to take MKL out of the lab and into the real world.
Authors (3) 1 from IIT Delhi
Publication Details
| Type | Conference Paper |
|---|---|
| Published | August 12, 2012 |
| DOI | 10.1145/2339530.2339648 |
| OpenAlex ID | W2146722014 |
| Open Access | Closed Access |
Research Topics
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