Adaptive Metric Dimensionality Reduction

@inproceedings{Gottlieb2013AdaptiveMD,
  title={Adaptive Metric Dimensionality Reduction},
  author={Lee-Ad Gottlieb and Aryeh Kontorovich and Robert Krauthgamer},
  booktitle={ALT},
  year={2013}
}
We study data-adaptive dimensionality reduction in the context of supervised learning in general metric spaces. Our main statistical contribution is a generalization bound for Lipschitz functions in metric spaces that are doubling, or nearly doubling, which yields a new theoretical explanation for empirically reported improvements gained by preprocessing Euclidean data by PCA (Principal Components Analysis) prior to constructing a linear classifier. On the algorithmic front, we describe an… CONTINUE READING

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