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NeuroCOLT
Technical Report NC-TR-99-053
The
consistency dimension and distribution-dependent learning from queries
(Extended abstract)
Balcązar,
Castro, Guijarro & Simon
Abstract
We
prove a new combinatorial characterization of polynomial learnability
from equivalence queries, and state some of its consequences relating
the learnability of a class with the learnability via equivalence
and membership queries of its subclasses obtained by restricting the
instance space. Then we propose and study two models of query learning
in which there is a probability distribution on the instance space,
both as an application of the tools developed from the combinatorial
characterization and as models of independent interest.
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