Cluster-based Kriging Approximation Algorithms for Complexity Reduction

4 Feb 2017Bas van SteinHao WangWojtek KowalczykMichael EmmerichThomas Bäck

Kriging or Gaussian Process Regression is applied in many fields as a non-linear regression model as well as a surrogate model in the field of evolutionary computation. However, the computational and space complexity of Kriging, that is cubic and quadratic in the number of data points respectively, becomes a major bottleneck with more and more data available nowadays... (read more)

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