Logistic regression with an auxiliary data source

@inproceedings{Liao2005LogisticRW,
  title={Logistic regression with an auxiliary data source},
  author={Xuejun Liao and Ya Xue and Lawrence Carin},
  booktitle={ICML},
  year={2005}
}
To achieve good generalization in supervised learning, the training and testing examples are usually required to be drawn from the same source distribution. In this paper we propose a method to relax this requirement in the context of logistic regression. Assuming <i>D<sup>p</sup></i> and <i>D<sup>a</sup></i> are two sets of examples drawn from two mismatched distributions, where <i>D<sup>a</sup></i> are fully labeled and <i>D<sup>p</sup></i> partially labeled, our objective is to complete the… CONTINUE READING
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