Video
Loading video...

📄 Conference Paper

SPF-GMKL

August 12, 2012 77 citations 🔒 Closed
77
Citations
3
Authors
37
References
2
Countries
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.

Publication Details
TypeConference Paper
PublishedAugust 12, 2012
DOI 10.1145/2339530.2339648
OpenAlex ID W2146722014
Open AccessClosed Access
Related Publications