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» Response modeling with support vector machines
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HAIS
2009
Springer
15 years 2 months ago
Pareto-Based Multi-output Model Type Selection
In engineering design the use of approximation models (= surrogate models) has become standard practice for design space exploration, sensitivity analysis, visualization and optimi...
Dirk Gorissen, Ivo Couckuyt, Karel Crombecq, Tom D...
IJCNN
2007
IEEE
15 years 3 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...
IJCNN
2006
IEEE
15 years 3 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
UAI
2000
14 years 11 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
80
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ICML
2006
IEEE
15 years 10 months ago
Two-dimensional solution path for support vector regression
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...
Gang Wang, Dit-Yan Yeung, Frederick H. Lochovsky