Learning separations by Boolean combinations of half-spaces

Given two subsets S/sub 1/ and S/sub 2/ (not necessarily finite) of R/sup d/ separable by a Boolean combination of N halfspaces, the authors consider the problem of learning the separation function from a finite set of examples. The solution consists of a system of N perceptrons and a single consoli...

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Bibliographic Details
Main Authors: Rao, N.S.V., Oblow, E.M., Glover, C.W.
Format: Conference Proceeding
Language:English
Subjects:
Argon
Computer science
Contracts
Ear
Intelligent systems
Laboratories
Polynomials
Probability distribution
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Summary:Given two subsets S/sub 1/ and S/sub 2/ (not necessarily finite) of R/sup d/ separable by a Boolean combination of N halfspaces, the authors consider the problem of learning the separation function from a finite set of examples. The solution consists of a system of N perceptrons and a single consolidator which combines the outputs of the individual perceptrons. The authors show that an off-line version of this problem where the examples are given in a batch, can be solved in time polynomial in the number of examples. The authors also provide an on-line learning algorithm that incrementally solves the problem by suitably training a system of N perceptrons much in the spirit of classical perceptron learning algorithm.< >
DOI:10.1109/ICPR.1992.201850