This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Sep 1993
Volume: 15,
Issue: 9
On page(s): 933-942
ISSN: 0162-8828
References Cited: 24
CODEN: ITPIDJ
INSPEC Accession Number: 4526022
DOI: 10.1109/34.232080
Posted online: 2002-08-06 18:43:51.0
Abstract
An extension of the standard probably approximately correct (PAC)
learning model that allows the use of generalized samples is introduced.
A generalized sample is viewed as a pair consisting of a functional on
the concept class together with the value obtained by the functional
operating on the unknown concept. It appears that this model can be
applied to a number of problems in signal processing and geometric
reconstruction to provide sample size bounds under a PAC criterion. A
specific application of the generalized model to a problem of curve
reconstruction is considered, and some connections with a result from
stochastic geometry are discussed
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