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Identifying the Machine Learning Family from Black-Box Models

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Identifying the Machine Learning Family from Black-Box Models

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Fabra-Boluda, R.; Ferri Ramírez, C.; Hernández-Orallo, J.; Martínez-Plumed, F.; Ramírez Quintana, MJ. (2018). Identifying the Machine Learning Family from Black-Box Models. Lecture Notes in Computer Science. 11160:55-65. https://doi.org/10.1007/978-3-030-00374-6_6

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/147681

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Title: Identifying the Machine Learning Family from Black-Box Models
Author: Fabra-Boluda, Raúl Ferri Ramírez, César Hernández-Orallo, José Martínez-Plumed, Fernando Ramírez Quintana, María José
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] We address the novel question of determining which kind of machine learning model is behind the predictions when we interact with a black-box model. This may allow us to identify families of techniques whose models ...[+]
Subjects: Machine learning families , Black-box model , Dissimilarity measures , Adversarial machine learning
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-00374-6_6
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-030-00374-6_6
Conference name: XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'18)
Conference place: Granada, España
Conference date: Octubre 23-26,2018
Project ID:
MECD/PRX17/00467
...[+]
MECD/PRX17/00467
GV/BEST/2017/045
GENERALITAT VALENCIANA/PROMETEOII/2015/013
MINISTERIO DE ECONOMIA Y EMPRESA/TIN2015-69175-C4-1-R
/FSA9550-17-1-0287
INST NAL DE CIBERSEGURIDAD DE ESPAÑA, S.A. /INCIBEI-2015-27345
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Thanks:
This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-17-1-0287, the EU (FEDER), and the Spanish MINECO under grant TIN 2015-69175-C4-1-R, the Generalitat ...[+]
Type: Artículo Comunicación en congreso Capítulo de libro

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