Transductive Minimax Probability Machine

@inproceedings{Huang2014TransductiveMP,
  title={Transductive Minimax Probability Machine},
  author={Gao Huang and Shiji Song and Zhixiang Eddie Xu and Kilian Q. Weinberger},
  booktitle={ECML/PKDD},
  year={2014}
}
The Minimax Probability Machine (MPM) is an elegant machine learning algorithm for inductive learning. It learns a classifier that minimizes an upper bound on its own generalization error. In this paper, we extend its celebrated inductive formulation to an equally elegant transductive learning algorithm. In the transductive setting, the label assignment of a test set is already optimized during training. This optimization problem is an intractable mixed-integer programming. Thus, we provide an… CONTINUE READING
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