Mining adversarial patterns via regularized loss minimization

@article{Liu2010MiningAP,
  title={Mining adversarial patterns via regularized loss minimization},
  author={Wei Liu and S. Chawla},
  journal={Machine Learning},
  year={2010},
  volume={81},
  pages={69-83}
}
  • Wei Liu, S. Chawla
  • Published 2010
  • Mathematics, Computer Science
  • Machine Learning
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is deliberately constructed in order to increase the error rates of the classifier. A prominent example is spam email where words are transformed to get around word based features embedded in a spam filter.In this paper we model the interaction between a data miner and an adversary as a Stackelberg game with convex loss… Expand
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