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» Multi-structure model selection via kernel optimisation
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CVPR
2010
IEEE
13 years 2 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang
ESANN
2007
13 years 6 months ago
Model Selection for Kernel Probit Regression
Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
Gavin C. Cawley
JMLR
2010
115views more  JMLR 2010»
12 years 11 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri
JMLR
2010
129views more  JMLR 2010»
12 years 11 months ago
Approximation of hidden Markov models by mixtures of experts with application to particle filtering
Selecting conveniently the proposal kernel and the adjustment multiplier weights of the auxiliary particle filter may increase significantly the accuracy and computational efficie...
Jimmy Olsson, Jonas Ströjby
IJCNN
2006
IEEE
13 years 10 months ago
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...
Gavin C. Cawley