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Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12590/16844
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dc.contributor.advisorOchoa Luna, Jose Eduardo-
dc.contributor.authorMuroya Lei, Stefanie-
dc.date.accessioned2021-09-15T01:23:27Z-
dc.date.available2021-09-15T01:23:27Z-
dc.date.issued2021-
dc.identifier.other1073395-
dc.identifier.urihttp://hdl.handle.net/20.500.12590/16844-
dc.description.abstractThe sampling task of Seq2Seq models in Natural Language Processing (NLP) is based on heuristics because of the Non-Deterministic Polynomial Time (NP) nature of this problem. The goal of this research is to develop a quantum sampler for Seq2Seq models, and give evidence that Quantum Annealing (QA) can guide the search space of these samplers. The contribution of this work is given by showing an architecture to represent Recurrent Neural Networks (RNN) in a quantum computer to finally develop a quantum sampler. The individual architectures (i.e. summation, multiplication, argmax, and activation functions) achieve optimal accuracies in both simulated and quantum environments. While the results of the overall proposal show that it can either outperform or match greedy approaches. As the very first steps of quantum NLP, these are tested against simple RNN with a synthetic data set of random numbers, and a real quantum computer is utilized. Since ane functions are the basis of most Artificial Intelligence (AI) models, this method can be applied to more complex architectures in the future.es_PE
dc.description.uriTesises_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherUniversidad Católica San Pabloes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.subjectQuantum Annealinges_PE
dc.subjectISING Modeles_PE
dc.subjectSamplinges_PE
dc.subjectNatural Language Processinges_PE
dc.subjectSeq2Seqes_PE
dc.titleQuantum exordium for natural language processing: A novel approach to sample on decoderses_PE
dc.typeinfo:eu-repo/semantics/bachelorThesises_PE
thesis.degree.nameLicenciado en Ciencia de la Computaciónes_PE
thesis.degree.grantorUniversidad Católica San Pablo. Departamento de Ciencia de la Computaciónes_PE
thesis.degree.levelTítulo Profesionales_PE
thesis.degree.disciplineCiencia de la Computaciónes_PE
thesis.degree.programPrograma Profesional de Ciencia de la Computaciónes_PE
renati.author.dni76923844-
dc.publisher.countryPEes_PE
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.02.01es_PE
renati.advisor.orcidhttps://orcid.org/0000-0002-8979-3785es_PE
renati.advisor.dni29738760-
renati.typehttps://purl.org/pe-repo/renati/type#tesises_PE
renati.levelhttps://purl.org/pe-repo/renati/level#tituloProfesionales_PE
renati.discipline611016es_PE
renati.jurorYván Jesús Túpac Valdiviaes_PE
renati.jurorJulio Omar Santisteban Pabloes_PE
Appears in Collections:Tesis Pregrado - Ciencia de la computación

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