NeuroCOLT

Neural Networks and Computational Learning Theory

 

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NeuroCOLT Technical Report NC-TR-95-048

 

The Complexity of Query Learning Minor Closed Graph Classes

Carlos Domingo
Tokyo Institute of Technology

John Shawe-Taylor
Royal Holloway, University of London

Abstract
The paper considers the problem of learning classes of graphs closed under taking minors. It is shown that any such class can be properly learned in polynomial time using membership and equivalence queries.  The representation of the class is in terms of a set of minimal excluded minors (obstruction set). Moreover, a negative result for learning such classes using only equivalence queries is also provided, after introducing a notion of reducibility between query learning problems.

 

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