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» Learning with Kernels and Logical Representations
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CVPR
2009
IEEE
15 years 4 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
ICML
2003
IEEE
14 years 10 months ago
A Kernel Between Sets of Vectors
In various application domains, including image recognition, it is natural to represent each example as a set of vectors. With a base kernel we can implicitly map these vectors to...
Risi Imre Kondor, Tony Jebara
ACL
2006
13 years 11 months ago
Using String-Kernels for Learning Semantic Parsers
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
Rohit J. Kate, Raymond J. Mooney
CVPR
2007
IEEE
14 years 11 months ago
Learning Kernel Expansions for Image Classification
Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
Fernando De la Torre, Oriol Vinyals
NIPS
2007
13 years 11 months ago
Learning with Transformation Invariant Kernels
This paper considers kernels invariant to translation, rotation and dilation. We show that no non-trivial positive definite (p.d.) kernels exist which are radial and dilation inv...
Christian Walder, Olivier Chapelle