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» Kernel Machines and Boolean Functions
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ASPDAC
2005
ACM
120views Hardware» more  ASPDAC 2005»
13 years 9 months ago
STACCATO: disjoint support decompositions from BDDs through symbolic kernels
Abstract— A disjoint support decomposition (DSD) is a representation of a Boolean function F obtained by composing two or more simpler component functions such that the component...
Stephen Plaza, Valeria Bertacco
ICPR
2008
IEEE
14 years 1 months ago
A least square kernel machine with box constraints
In this paper, we present a least square kernel machine with box constraints (LSKMBC). The existing least square machines assume Gaussian hyperpriors and subsequently express the ...
Jayanta Basak
IJCNN
2007
IEEE
14 years 1 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...
SCIA
2005
Springer
137views Image Analysis» more  SCIA 2005»
14 years 29 days ago
Invariance in Kernel Methods by Haar-Integration Kernels
Abstract. We address the problem of incorporating transformation invariance in kernels for pattern analysis with kernel methods. We introduce a new class of kernels by so called Ha...
Bernard Haasdonk, A. Vossen, Hans Burkhardt
ML
2002
ACM
146views Machine Learning» more  ML 2002»
13 years 7 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio