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COLT
2003
Springer

Learning Random Log-Depth Decision Trees under the Uniform Distribution

10 years 3 months ago
Learning Random Log-Depth Decision Trees under the Uniform Distribution
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an inverse polynomial fraction of such trees using only uniformly distributed random examples from {0, 1}n . The learning algorithm constructs a decision tree as its hypothesis.
Jeffrey C. Jackson, Rocco A. Servedio
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where COLT
Authors Jeffrey C. Jackson, Rocco A. Servedio
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