Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Herrera Triguero, Francisco"'
Autor:
Aguilera Martos, Ignacio, García Vico, Ángel Miguel, Luengo Martín, Julián, Damas Arroyo, Sergio, Melero Rus, Francisco Javier, Valle-Alonso, José Javier, Herrera Triguero, Francisco
The combination of convolutional and recurrent neural networks is a promising framework. This arrangement allows the extraction of high-quality spatio-temporal features together with their temporal dependencies. This fact is key for time series predi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::de5ccacd3d0103ea9d5883601ee04fa7
https://doi.org/10.1016/j.neucom.2022.10.062
https://doi.org/10.1016/j.neucom.2022.10.062
Financial support of Tracasa Instrumental (iTRACASA) and of the Gobierno de Navarra - Departamento de Universidad, Innovación y Transformación Digital, as well as that of the Spanish Ministry of Science (project PID2019-108392GB-I00 (AEI/10.13039/5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::c9121ab8fd6ede791b54fbb4a4a9f08d
https://hdl.handle.net/10481/83517
https://hdl.handle.net/10481/83517
Publikováno v:
International Journal of Intelligent Systems.
This work was supported by the Spanish Ministry of Science and Technology under project PID2020-119478GB-I00 financed by \\ MCIN/AEI/10.13039/501100011033. This work was also partially supported by the Contract UGR-AM OTRI-6717 and the Contract UGR-A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::acb9ea359d2ae2e361e15dedc9aab831
Autor:
Carrasco Castillo, Jacinto, López Pretel, David, Aguilera Martos, Ignacio, García Gil, Diego Jesús, Luengo Martín, Julián, Herrera Triguero, Francisco|||0000-0002-7283-312X
Publikováno v:
Digibug. Repositorio Institucional de la Universidad de Granada
instname
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This work has been partially supported by the Ministry of Science and Technology under project TIN2017-89517-P, the Contract UGR-AM OTRI-4260 and the Andalusian Excellence project P18-FR-4961. J. Carrasco was supported by the Spanish Ministry of Scie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9b61cf4b1202ba6e9efbb00bdf1304b2
http://hdl.handle.net/10481/71033
http://hdl.handle.net/10481/71033
Autor:
Rodríguez Barroso, Nuria, Jiménez López, Daniel, Ruiz Millán, José Antonio, Martínez Cámara, Eugenio, Luzón García, María Victoria, Herrera Triguero, Francisco
The high demand of artificial intelligence services at the edges that also preserve data privacy has pushed the research on novel machine learning paradigms that fit these requirements. Federated learning has the ambition to protect data privacy thro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::07a67a169263b4eeaecb9a1f7db72fba
https://hdl.handle.net/10481/77990
https://hdl.handle.net/10481/77990
Autor:
Wu, Yuzhu, Herrera Triguero, Francisco
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic repres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::ba82cda309e70dbc0141715c57c8f4d0
https://hdl.handle.net/10481/77984
https://hdl.handle.net/10481/77984
Autor:
Gorriz Sáez, Juan Manuel, Ramírez Pérez De Inestrosa, Javier, Segovia Román, Fermín, Charte Luque, Francisco David, Herrera Triguero, Francisco
Arti cial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::f5bcdf3159639043232a3a487994a8cb
https://hdl.handle.net/10481/77987
https://hdl.handle.net/10481/77987
Autor:
Barredo Arrieta, Alejandro, Tabik, Siham, García López, Salvador, Molina Cabrera, Daniel, Herrera Triguero, Francisco
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in Machine Learning,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1648::c798f3a7f60493b3b2ad9682db0b507a
https://hdl.handle.net/10481/77982
https://hdl.handle.net/10481/77982
Autor:
Fernández Hilario, Alberto Luis, García López, Salvador, Herrera Triguero, Francisco, Chawla, Nitesh V.
Publikováno v:
Digibug. Repositorio Institucional de la Universidad de Granada
instname
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The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is considered \de facto" standard in the framework of learning from imbalanced data. This is due to its simplicity in the design of the procedure, as well as its robustness
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::17b16a1b3daf06b1ae4296cff209a796
http://hdl.handle.net/10481/56411
http://hdl.handle.net/10481/56411
Autor:
Herrera Triguero, Francisco
Publikováno v:
E-Prints Complutense: Archivo Institucional de la UCM
Universidad Complutense de Madrid
E-Prints Complutense. Archivo Institucional de la UCM
instname
Universidad Complutense de Madrid
E-Prints Complutense. Archivo Institucional de la UCM
instname
En esta conferencia presentaré mis reflexiones sobre la organización del trabajo de investigación y la producción científica, analizando las decisiones que día a día tenemos que tomar en el seno de un grupo de investigación: Introducción, in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5955c2cd8e33658f990dc4ed64addcd7
https://eprints.ucm.es/id/eprint/26466/
https://eprints.ucm.es/id/eprint/26466/