Discrete Chebyshev Classifiers

@inproceedings{Eban2014DiscreteCC,
  title={Discrete Chebyshev Classifiers},
  author={Elad Eban and Elad Mezuman and Amir Globerson},
  booktitle={ICML},
  year={2014}
}
In large scale learning problems it is often easy to collect simple statistics of the data, but hard or impractical to store all the original data. A key question in this setting is how to construct classifiers based on such partial information. One traditional approach to the problem has been to use maximum entropy arguments to induce a complete distribution on variables from statistics. However, this approach essentially makes conditional independence assumptions about the distribution, and… CONTINUE READING

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