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ICML
2004
IEEE
14 years 5 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
DAGM
2008
Springer
13 years 6 months ago
A Multiple Kernel Learning Approach to Joint Multi-class Object Detection
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Christoph H. Lampert, Matthew B. Blaschko
ICML
2009
IEEE
14 years 5 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
BMCBI
2008
228views more  BMCBI 2008»
13 years 4 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
BMCBI
2010
182views more  BMCBI 2010»
13 years 4 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...