{"id":1702,"date":"2022-06-11T10:17:59","date_gmt":"2022-06-11T08:17:59","guid":{"rendered":"https:\/\/www-staging.systransoft.com\/papers\/et-ut-non-rerum-nobis\/"},"modified":"2023-11-16T18:21:30","modified_gmt":"2023-11-16T17:21:30","slug":"et-ut-non-rerum-nobis","status":"publish","type":"paper","link":"https:\/\/www-staging.systransoft.com\/es\/recursos\/papers-and-publications\/et-ut-non-rerum-nobis\/","title":{"rendered":"Adaptaci\u00f3n multidominio en traducci\u00f3n autom\u00e1tica neuronal con estrategias de muestreo din\u00e1mico"},"content":{"rendered":"Building effective Neural Machine Translation models often implies accommodating diverse sets of heterogeneous data so as to optimize performance for the domain(s) of interest. Such multi-source \/ multi-domain adaptation problems are typically approached through instance selection or reweighting strategies, based on a static assessment of the relevance of training instances with respect to the task at hand. In this paper, we study dynamic data selection strategies that are able to automatically re-evaluate the usefulness of data samples and to evolve a data selection policy in the course of training. Based on the results of multiple experiments, we show that such methods constitute a generic framework to automatically and effectively handle a variety of real-world situations, from multi-source domain adaptation to multi-domain learning and unsupervised domain adaptation.","protected":false},"excerpt":{"rendered":"<p>La construcci\u00f3n de modelos efectivos de traducci\u00f3n autom\u00e1tica neuronal a menudo implica acomodar diversos conjuntos de datos heterog\u00e9neos para optimizar el rendimiento para el dominio o dominios de inter\u00e9s. Tales problemas de adaptaci\u00f3n de m\u00faltiples fuentes\/dominios se abordan normalmente a trav\u00e9s de estrategias de selecci\u00f3n o reponderaci\u00f3n de instancias, basadas en una evaluaci\u00f3n est\u00e1tica de la pertinencia de las instancias de capacitaci\u00f3n con respecto a la tarea ... <a href=\"https:\/\/www-staging.systransoft.com\/es\/recursos\/papers-and-publications\/et-ut-non-rerum-nobis\/\">Continuaci\u00f3n<\/a><\/p>","protected":false},"featured_media":0,"template":"","class_list":["post-1702","paper","type-paper","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www-staging.systransoft.com\/es\/wp-json\/wp\/v2\/paper\/1702","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www-staging.systransoft.com\/es\/wp-json\/wp\/v2\/paper"}],"about":[{"href":"https:\/\/www-staging.systransoft.com\/es\/wp-json\/wp\/v2\/types\/paper"}],"wp:attachment":[{"href":"https:\/\/www-staging.systransoft.com\/es\/wp-json\/wp\/v2\/media?parent=1702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}