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Aprendizaje multitarea mediante arquitecturas neuronales basadas en subredes privadas
dc.contributor.author | García Laencina, Pedro José | |
dc.contributor.author | Verdú Monedero, Rafael | |
dc.contributor.author | Sancho Gómez, José Luis | |
dc.date.accessioned | 2009-02-12T08:45:17Z | |
dc.date.available | 2009-02-12T08:45:17Z | |
dc.date.issued | 2005-09 | |
dc.identifier.citation | GARCÍA LAENCINA, Pedro José; VERDÚ MONEDERO, Rafael y SÁNCHO GÓMEZ, José Luis. Aprendizaje multitarea mediante arquitecturas neuronales basadas en subredes privadas. En: Simposium Nacional de la Unión Científica Internacional de Radio (20º: 2005: Gandía) XX Simposium Nacional de la URSI 2005. URSI 05, Gandía 14-16 de Septiembre 2005. Gandía: Universidad Politécnica de Valencia, 2005 | es |
dc.description.abstract | Human learning frequently involves learning several tasks simultaneously; in particular, humans compare and contrast similar tasks for solving a problem. Nevertheless, most approaches to machine learning focus on the learning of a single isolated task, Single Task Learning (STL). Most of them can be formulated from learning several tasks related to the main task at the same time while using a shared representation, Multitask Learning (MTL). This type of learning improves generalization performance for a main task by using the information contained in other related tasks. In this article, we examine distinct schemes used in MTL, propose an new network architecture and test each scheme in two different problems. The proposed scheme makes use of private subnetworks to improve the performance of MTL. | es |
dc.description.sponsorship | Este trabajo está parcialmente financiado por el Ministerio de Educación y Ciencia a través del proyecto TIC2002-03033. | es |
dc.format | application/pdf | |
dc.language.iso | spa | es |
dc.publisher | Universidad Politécnica de Valencia | es |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.title | Aprendizaje multitarea mediante arquitecturas neuronales basadas en subredes privadas | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.subject.other | Teoría de la Señal y las Comunicaciones | es |
dc.subject | Modelos duales | es |
dc.subject | Aprendizaje multitarea | es |
dc.subject | Arquitecturas neuronales | es |
dc.subject | Arquitectura asimétrica | es |
dc.identifier.uri | http://hdl.handle.net/10317/702 |
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