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REPORTS > AUTHORS > KENSEI TSUCHIDA:
All reports by Author Kensei Tsuchida:

TR96-061 | 27th November 1996
Ryuhei Uehara, Kensei Tsuchida, Ingo Wegener

Optimal attribute-efficient learning of disjunction, parity, and threshold functions

Decision trees are a very general computation model.
Here the problem is to identify a Boolean function $f$ out of a given
set of Boolean functions $F$ by asking for the value of $f$ at adaptively
chosen inputs.
For classes $F$ consisting of functions which may be obtained from one
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