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We study polynomial time learning algorithms for Multiplicity Automata (MA) and Multiplicity Automata Function (MAF) that minimize the access to one or more of the following resources: Equivalence queries, Membership queries or Arithmetic operations in the field . This is in particular interesting when access to one or more of the above resources is significantly more expensive than the...
We study the learning models defined in [D. Angluin, M. Krikis, R.H. Sloan, G. Turán, Malicious omissions and errors in answering to membership queries, Machine Learning 28 (2–3) (1997) 211–255]: Learning with equivalence and limited membership queries and learning with equivalence and malicious membership queries.We show that if a class of concepts that is closed under projection is learnable in...
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