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dc.contributor.authorMarroquin, J. L.
dc.date.accessioned2008-04-15T15:55:37Z
dc.date.available2008-04-15T15:55:37Z
dc.date.issued1983-07
dc.identifier.urihttp://hdl.handle.net/1721.1/41200
dc.description.abstractIn this paper we analyse several approaches to the design of Cooperative Algorithms for solving a general problem: That of computing the values of some property over a spatial domain, when these values are constrained (but not uniquely determined) by some observations, and by some a priori knowledge about the nature of the solution (smoothness, for example). Specifically, we discuss the use of: Variational techniques; stochastic approximation methods for global optimization, and linear threshold networks. Finally, we present a new approach, based on the interconnection of Winner-take-all networks, for which it is possible to establish precise convergence results, including bounds on the rate of convergence.en
dc.description.sponsorshipMIT Artificial Intelligence Laboratoryen
dc.language.isoen_USen
dc.publisherMIT Artificial Intelligence Laboratoryen
dc.relation.ispartofseriesMIT Artificial Intelligence Laboratory Working Papers, WP-253en
dc.titleDesign of Cooperative Networksen
dc.typeWorking Paperen


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