A Gaussian Process Robust Regression

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概要

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• A modified Gaussian process regression is proposed aiming at making regressors robust against outliers. The proposed method is based on U-loss, which is introduced as a natural extension of Kullback-Leibler divergence. The robustness is examined based on the influence function, and numerical experiments are conducted for contaminated data sets and it is shown that the practical performance agrees with the theoretical analysis.

• 理論物理学刊行会の論文
• 2005-04-30

著者

• KURODA Yusuke

  Nomura Research Institute

• Murata Noboru

  School Of Science And Engineering Waseda University

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• A Gaussian Process Robust Regression

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