1854 search results - page 41 / 371 » On Kernel Methods for Relational Learning |
CIDM
2007
IEEE
15 years 1 months ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
ICDM
2003
IEEE
15 years 3 months ago
2003
IEEE
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
ESA
2006
Springer
15 years 1 months ago
2006
Springer
Much recent work in the theoretical computer science, linear algebra, and machine learning has considered matrix decompositions of the following form: given an m
JMLR
2010
14 years 4 months ago
2010
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
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FTCGV
2011
14 years 1 months ago
2011
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...