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» Extensions of Manifold Learning Algorithms in Kernel Feature...
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ALT
2001
Springer
14 years 4 months ago
Learning of Boolean Functions Using Support Vector Machines
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
Ken Sadohara
NIPS
2003
13 years 9 months ago
Learning to Find Pre-Images
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Gökhan H. Bakir, Jason Weston, Bernhard Sch&o...
JMLR
2010
206views more  JMLR 2010»
13 years 2 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
CVPR
2009
IEEE
15 years 2 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
PAMI
2008
135views more  PAMI 2008»
13 years 7 months ago
MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
Zhe Wang, Songcan Chen, Tingkai Sun