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» Core Vector Regression for very large regression problems
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IJCNN
2007
IEEE
14 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
CVPR
2010
IEEE
14 years 4 months ago
SVM for Edge-Preserving Filtering
In this paper, we propose a new method to construct an edge-preserving filter which has very similar response to the bilateral filter. The bilateral filter is a normalized convolu...
Qingxiong Yang, Shengnan Wang, Narendra Ahuja
VLSI
2007
Springer
14 years 1 months ago
Estimating design time for system circuits
System design complexity is growing rapidly. As a result, current development costs are constantly increasing. It is becoming increasingly difficult to estimate how much time it ...
Cyrus Bazeghi, Francisco J. Mesa-Martinez, Brian G...
BMCBI
2010
182views more  BMCBI 2010»
13 years 7 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...
BMCBI
2007
194views more  BMCBI 2007»
13 years 7 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung