| Learning under Model Misspecification: Applications to Variational and Ensemble methods A Masegosa Advances in Neural Information Processing Systems 33, 2020 | 123 | 2020 |
| Requirements for total uncertainty measures in Dempster–Shafer theory of evidence J Abellán, A Masegosa International journal of general systems 37 (6), 733-747, 2008 | 105 | 2008 |
| A method for integrating expert knowledge when learning Bayesian networks from data A Cano, AR Masegosa, S Moral IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011 | 96 | 2011 |
| An interactive approach for Bayesian network learning using domain/expert knowledge AR Masegosa, S Moral International Journal of Approximate Reasoning 54 (8), 1168-1181, 2013 | 95 | 2013 |
| Bagging decision trees on data sets with classification noise J Abellán, AR Masegosa International Symposium on Foundations of Information and Knowledge Systems …, 2010 | 89 | 2010 |
| Diversity and Generalization in Neural Network Ensembles LA Ortega, R Cabañas, A Masegosa International Conference on Artificial Intelligence and Statistics, 11720-11743, 2022 | 81 | 2022 |
| Bagging schemes on the presence of class noise in classification J Abellán, AR Masegosa Expert Systems with Applications 39 (8), 6827-6837, 2012 | 81 | 2012 |
| An ensemble method using credal decision trees J Abellan, AR Masegosa European journal of operational research 205 (1), 218-226, 2010 | 67 | 2010 |
| Second order PAC-Bayesian bounds for the weighted majority vote A Masegosa, S Lorenzen, C Igel, Y Seldin Advances in Neural Information Processing Systems 33, 2020 | 61 | 2020 |
| Classification with decision trees from a nonparametric predictive inference perspective J Abellán, RM Baker, F Coolen, RJ Crossman, AR Masegosa Computational Statistics & Data Analysis 71, 789-802, 2014 | 43 | 2014 |
| Modeling concept drift: A probabilistic graphical model based approach H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ... Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015 | 39 | 2015 |
| An experimental study about simple decision trees for bagging ensemble on datasets with classification noise J Abellán, AR Masegosa European Conference on Symbolic and Quantitative Approaches to Reasoning and …, 2009 | 38 | 2009 |
| Learning from incomplete data in Bayesian networks with qualitative influences AR Masegosa, AJ Feelders, LC van der Gaag International Journal of Approximate Reasoning 69, 18-34, 2016 | 37 | 2016 |
| Imprecise classification with credal decision trees J Abellán, AR Masegosa International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2012 | 36 | 2012 |
| New skeleton-based approaches for Bayesian structure learning of Bayesian networks AR Masegosa, S Moral Applied Soft Computing 13 (2), 1110-1120, 2013 | 33 | 2013 |
| From anecdote to evidence: the relationship between personality and need for cognition of developers D Russo, AR Masegosa, KJ Stol Empirical Software Engineering 27 (3), 71, 2022 | 32 | 2022 |
| Analyzing concept drift: A case study in the financial sector AR Masegosa, AM Martínez, D Ramos-López, H Langseth, TD Nielsen, ... Intelligent Data Analysis 24 (3), 665-688, 2020 | 31 | 2020 |
| AMIDST: A Java toolbox for scalable probabilistic machine learning AR Masegosa, AM Martínez, D Ramos-López, R Cabañas, A Salmerón, ... Knowledge-Based Systems 163, 595-597, 2019 | 28 | 2019 |
| Bayesian models of data streams with hierarchical power priors A Masegosa, TD Nielsen, H Langseth, D Ramos-López, A Salmerón, ... Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 26 | 2017 |
| Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks AR Masegosa, S Moral International Journal of Approximate Reasoning 55 (7), 1548-1569, 2014 | 23 | 2014 |
Serafín MoralDept. Computer Science and Artificial Intelligence, University of GranadaVerified email at decsai.ugr.es
