Generative Local Metric Learning for Nearest Neighbor Classification

@article{Noh2010GenerativeLM,
  title={Generative Local Metric Learning for Nearest Neighbor Classification},
  author={Yung-Kyun Noh and Byoung-Tak Zhang and Daniel D. Lee},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2010},
  volume={40},
  pages={106-118}
}
We consider the problem of learning a local metric in order to enhance the performance of nearest neighbor classification. Conventional metric learning methods attempt to separate data distributions in a purely discriminative manner; here we show how to take advantage of information from parametric generative models. We focus on the bias in the information-theoretic error arising from finite sampling effects, and find an appropriate local metric that maximally reduces the bias based upon… CONTINUE READING
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