Learning Decision Trees Using the Fourier Sprectrum (Extended Abstract)

@inproceedings{Kushilevitz1991LearningDT,
  title={Learning Decision Trees Using the Fourier Sprectrum (Extended Abstract)},
  author={Eyal Kushilevitz and Yishay Mansour},
  booktitle={STOC},
  year={1991}
}
This work gives a polynomial time algcmithm for learning decision trees with respect tc~ the uniform distribution. (This algorithm uses membership queries.) The decision tree model that we consider is an extension of the traditional boolean decision tree model, and allows linear operations in each node (i.e. summation of a subset of the input variables over G1’(2)). We show how to learn in polynomial time any function that can be approximated (in norm L2) by a polynomially sparse function (i.e… CONTINUE READING
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