Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 312073.0, MPI für biologische Kybernetik / Biologische Kybernetik
Large Scale Multiple Kernel Learning
Authors:Sonnenburg, S.; Rätsch, G.; Schäfer, C.; Schölkopf, B.
Date of Publication (YYYY-MM-DD):2006-07
Title of Journal:Journal of Machine Learning Research
Volume:7
Start Page:1531
End Page:1565
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for classification, leading to a convex quadratically constrained quadratic program. We
show that it can be rewritten as a semi-infinite linear program that can be efficiently solved by recycling the standard SVM implementations. Moreover, we generalize the formulation and our method to a larger class of problems, including regression and one-class classification. Experimental results show that the proposed algorithm works for hundred thousands of examples or hundreds of
kernels to be combined, and helps for automatic model selection, improving the interpretability of
the learning result. In a second part we discuss general speed up mechanism for SVMs, especially
when used with sparse feature maps as appear for string kernels, allowing us to train a string kernel
SVM on a 10 million real-world splice data set from computational biology. We integrated multiple kernel learning in our machine learning toolbox SHOGUN for which the source code is publicly
available at http://www.fml.tuebingen.mpg.de/raetsch/projects/shogun.
External Publication Status:published
Document Type:Article
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:3994
URL:http://jmlr.csail.mit.edu/papers/volume7/sonnenbur...
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.