State Space Realization Theorems For Data Mining

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dc.creatorGrossman, Robert L
dc.creatorLarson, Richard G
dc.date2009-01-18
dc.date.accessioned2026-07-07T12:31:33Z
dc.date.available2026-07-07T12:31:33Z
dc.descriptionIn this paper, we consider formal series associated with events, profiles derived from events, and statistical models that make predictions about events. We prove theorems about realizations for these formal series using the language and tools of Hopf algebras.
dc.identifierhttps://arxiv.org/abs/0901.2735
dc.identifierhttp://arxiv.org/abs/0901.2735
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/216479
dc.subjectMachine Learning
dc.subjectRings and Algebras
dc.subjectStatistics Theory
dc.subject62A01; 16W30
dc.titleState Space Realization Theorems For Data Mining
dc.typetext

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