Listar por autor "Urda, Daniel"
Mostrando ítems 1-4 de 4
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Classification of high dimensional data using LASSO ensembles
The estimation of multivariable predictors with good performance in high dimensional settings is a crucial task in biomedical contexts. Usually, solutions based on the application of a single machine ... -
Deep Learning to Analyze RNA-Seq Gene Expression Data
Urda, Daniel; Montes-Torres, Julio
; Moreno, Fernando; Franco, Leonardo; Jerez-Aragonés, José Manuel (Springer, 2017)
Deep learning models are currently being applied in several areas with great success. However, their application for the analysis of high-throughput sequencing data remains a challenge for the research community due to ... -
Energy-efficient reprogramming in wsn using constructive neural networks.
Urda, Daniel; Cañete, Eduardo; Subirats Contreras, José Luis; Franco, Leónardo; Llopis-Torres, Luis Manuel; Jerez-Aragonés, José Manuel[et al.] (International Journal of Innovative Computing, Information and Control, 2012-11)
In this paper, we propose the use of neural based technologies to carry out the dynamic reprogramming of wireless sensor networks as an alternative to traditional methodology. An analysis an comparison of the energy cost ... -
Machine learning models to search relevant genetic signatures in clinical context
Urda, Daniel; Luque-Baena, Rafael Marcos; Franco, Leonardo; Sánchez-Maroño, Noelia; Jerez-Aragonés, José Manuel (2017-06-26)
Clinicians are interested in the estimation of robust and relevant genetic signatures from gene sequencing data. Many machine learning approaches have been proposed trying to address well-known issues of this complex ...