idUS - Author profile: Sillero Denamiel, María Remedios

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Name	Sillero Denamiel, María Remedios
Department	Estadística e Investigación Operativa
Knowledge area	Estadística e Investigación Operativa
Professional category	Profesora Ayudante Doctora
E-mail	Request

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10
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1042
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Publications
Article The tree based linear regression model for hierarchical categorical variables Carrizosa Priego, Emilio José; Hvas Mortensen, Laust; Romero Morales, María Dolores; Sillero Denamiel, María Remedios (Elsevier, 2022) Many real-life applications consider nominal categorical predictor variables that have a hierarchical structure, e.g. ...
Article On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19 Benítez Peña, Sandra; Carrizosa Priego, Emilio José; Guerrero, Vanesa; Jiménez Gamero, María Dolores; Martín Barragán, Belén; Molero Río, Cristina; Ramírez Cobo, Josefa; Romero Morales, María Dolores; Sillero Denamiel, María Remedios (Elsevier, 2021) Since the seminal paper by Bates and Granger in 1969, a vast number of ensemble methods that combine different base ...
Article Constrained Naïve Bayes with application to unbalanced data classification Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa; Sillero Denamiel, María Remedios (Springer, 2021) The Naïve Bayes is a tractable and efficient approach for statistical classification. In general classification problems, ...
PhD Thesis Computational Methods for the Analysis of Complex Data Sillero Denamiel, María Remedios; Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa (2021) This PhD dissertation bridges the disciplines of Operations Research and Statistics to develop novel computational methods ...
Article Variable selection for Naïve Bayes classification Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa; Sillero Denamiel, María Remedios (Pergamon-Elsevier Science Ltd., 2021) The Naïve Bayes has proven to be a tractable and efficient method for classification in multivariate analysis. However, ...
Article Variable selection for Naïve Bayes classification Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa; Sillero Denamiel, María Remedios (Elsevier, 2021) The Naïve Bayes has proven to be a tractable and efficient method for classification in multivariate analysis. However, ...
Article A cost-sensitive constrained Lasso Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa; Sillero Denamiel, María Remedios (Springer, 2020) The Lasso has become a benchmark data analysis procedure, and numerous variants have been proposed in the literature. ...
Article Identification problem in plug-flow chemical reactors using the adjoint method Bermúdez, A.; Esteben, N.; Ferrín, J.L.; Rodríguez Calo, J.F.; Sillero Denamiel, María Remedios (Elsevier, 2016) The aim of this work is to solve identification problems in plug-flow chemical reactors. For this purpose an adjoint-based ...
Article On Extreme Concentrations in Chemical Reaction Networks with Incomplete Measurements Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Chis, Oana; Esteban, Noemí; Jiménez Cordero, María Asunción; Rodríguez, José Francisco; Sillero Denamiel, María Remedios (ACS, 2016) A fundamental problem in the analysis of chemical reactions networks consists of identifying concentration values along ...
Master's Final Project A new multivariate data analysis model: constrained Naïve Bayes Sillero Denamiel, María Remedios; Blanquero Bravo, Rafael; Carrizosa Priego, Emilio José; Ramírez Cobo, Josefa (2016)