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Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among other domains. In this paper, we show how to estimate these conditional quantile functions within a Bayes risk minimization framework using a Gaussian process prior. The resulting non-parametric probabilistic model is easy...
In this paper we consider the weighted (1-center) location problems weighted by the possibilistic clustering method. Such weighting method leads to better robustness to outliers compared with minimax location estimation. Its effectiveness was further verified by the experiments on the artificial dataset.
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