ChapBoltzmann Machines Learning Using High Order Decimation

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dc.contributor.authorEnric Farguell
dc.contributor.authorF. Mazzanti
dc.contributor.authorE. Gómez-Ramı́rez
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T20:23:13Z
dc.date.available2026-03-22T20:23:13Z
dc.date.issued2007
dc.descriptionCitaciones: 1
dc.identifier.doi10.1007/978-3-540-37421-3_2
dc.identifier.urihttps://doi.org/10.1007/978-3-540-37421-3_2
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/81688
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.ispartofStudies in fuzziness and soft computing
dc.sourceUniversitat Ramon Llull
dc.subjectDecimation
dc.subjectBoltzmann machine
dc.subjectRestricted Boltzmann machine
dc.subjectContext (archaeology)
dc.subjectComputer science
dc.subjectArtificial neural network
dc.subjectDegrees of freedom (physics and chemistry)
dc.subjectArtificial intelligence
dc.subjectTopology (electrical circuits)
dc.subjectFeature (linguistics)
dc.titleChapBoltzmann Machines Learning Using High Order Decimation
dc.typebook-chapter

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