Ana M. Martínez
Ana M. Martínez
Joint Research Center, European Commission
Verified email at
Cited by
Cited by
Scalable Learning of Bayesian Network Classifiers
AM Martinez, GI Webb, S Chen, NA Zaidi
Journal of Machine Learning Research 17, 1-35, 2016
Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter?
MJ Flores, JA Gámez, AM Martínez, JM Puerta
Applied Intelligence 34, 372-385, 2011
Domains of competence of the semi-naive Bayesian network classifiers
MJ Flores, JA Gámez, AM Martínez
Information Sciences 260, 120-148, 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
GAODE and HAODE: two proposals based on AODE to deal with continuous variables
MJ Flores, JA Gámez, AM Martínez, JM Puerta
Proceedings of the 26th annual international conference on machine learning …, 2009
Sample-Based Attribute Selective A DE for Large Data
S Chen, AM Martinez, GI Webb, L Wang
IEEE Transactions on Knowledge and Data Engineering 29 (1), 172-185, 2016
Supervised Classification with Bayesian Networks: A Review on Models and Applications
MJ Flores, JA Gámez, AM Martínez
Intelligent Data Analysis for Real-Life Applications: Theory and Practice …, 2012
Selective AnDE for large data learning: a low-bias memory constrained approach
S Chen, AM Martínez, GI Webb, L Wang
Knowledge and Information Systems 50, 475-503, 2017
AMIDST: A Java toolbox for scalable probabilistic machine learning
AR Masegosa, AM Martinez, D Ramos-López, R Cabańas, A Salmerón, ...
Knowledge-Based Systems 163, 595-597, 2019
Highly scalable attribute selection for averaged one-dependence estimators
S Chen, AM Martinez, GI Webb
Advances in Knowledge Discovery and Data Mining: 18th Pacific-Asia …, 2014
Probabilistic graphical models on multi-core CPUs using Java 8
AR Masegosa, AM Martinez, H Borchani
IEEE Computational Intelligence Magazine 11 (2), 41-54, 2016
HODE: Hidden one-dependence estimator
MJ Flores, JA Gámez, AM Martínez, JM Puerta
Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 10th …, 2009
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
Scaling up Bayesian variational inference using distributed computing clusters
AR Masegosa, AM Martinez, H Langseth, TD Nielsen, A Salmerón, ...
International Journal of Approximate Reasoning 88, 435-451, 2017
d-VMP: Distributed Variational Message Passing
AR Masegosa, AM Martínez, H Langseth, TD Nielsen, A Salmerón, ...
Proceedings of the Eighth International Conference on Probabilistic …, 2016
Analyzing the impact of the discretization method when comparing Bayesian classifiers
MJ Flores, JA Gámez, AM Martínez, JM Puerta
Trends in Applied Intelligent Systems: 23rd International Conference on …, 2010
Parallel importance sampling in conditional linear Gaussian networks
A Salmerón, D Ramos-López, H Borchani, AM Martínez, AR Masegosa, ...
Advances in Artificial Intelligence: 16th Conference of the Spanish …, 2015
Mixture of truncated exponentials in supervised classification: Case study for the naive Bayes and averaged one-dependence estimators classifiers
MJ Flores, JA Gámez, AM Martínez, A Salmerón
2011 11th International Conference on Intelligent Systems Design and …, 2011
MAP inference in dynamic hybrid Bayesian networks
D Ramos-López, AR Masegosa, AM Martínez, A Salmerón, TD Nielsen, ...
Progress in Artificial Intelligence 6, 133-144, 2017
Financial data analysis with PGMs using AMIDST
R Cabańas, AM Martínez, AR Masegosa, D Ramos-López, A Samerón, ...
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016
The system can't perform the operation now. Try again later.
Articles 1–20