Corpus ID: 447246

Gaussian Process Quantile Regression using Expectation Propagation

@article{Boukouvalas2012GaussianPQ,
  title={Gaussian Process Quantile Regression using Expectation Propagation},
  author={A. Boukouvalas and R. Barillec and D. Cornford},
  journal={ArXiv},
  year={2012},
  volume={abs/1206.6391}
}
  • A. Boukouvalas, R. Barillec, D. Cornford
  • Published 2012
  • Mathematics, Computer Science
  • ArXiv
  • Direct quantile regression involves estimating a given quantile of a response variable as a function of input variables. We present a new framework for direct quantile regression where a Gaussian process model is learned, minimising the expected tilted loss function. The integration required in learning is not analytically tractable so to speed up the learning we employ the Expectation Propagation algorithm. We describe how this work relates to other quantile regression methods and apply the… CONTINUE READING

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