Ana M. Martínez
Ana M. Martínez
Large-Scale Data Specialist, Vestas
Verified email at vestas.com
Title
Cited by
Cited by
Year
Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter?
MJ Flores, JA Gámez, AM Martínez, JM Puerta
Applied Intelligence 34 (3), 372-385, 2011
472011
Scalable Learning of Bayesian Network Classifiers
AM Martinez, GI Webb, S Chen, NA Zaidi
Journal of Machine Learning Research 17, 1-35, 2016
402016
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
272009
Domains of competence of the semi-naive Bayesian network classifiers
MJ Flores, JA Gámez, AM Martínez
Information Sciences 260, 120-148, 2014
212014
Modeling concept drift: A probabilistic graphical model based approach
H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ...
International Symposium on Intelligent Data Analysis, 72-83, 2015
182015
HODE: Hidden one-dependence estimator
MJ Flores, JA Gámez, AM Martínez, JM Puerta
European Conference on Symbolic and Quantitative Approaches to Reasoning and …, 2009
152009
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
132016
Parallel importance sampling in conditional linear Gaussian networks
A Salmerón, D Ramos-López, H Borchani, AM Martínez, AR Masegosa, ...
Conference of the Spanish Association for Artificial Intelligence, 36-46, 2015
132015
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
132012
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
112017
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 (2), 475-503, 2017
112017
Amidst: a Java toolbox for scalable probabilistic machine learning
AR Masegosa, AM Martínez, D Ramos-López, R Cabańas, A Salmerón, ...
arXiv preprint arXiv:1704.01427, 2017
92017
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
92016
Dynamic Bayesian modeling for risk prediction in credit operations.
H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ...
SCAI, 17-26, 2015
92015
Highly scalable attribute selection for averaged one-dependence estimators
S Chen, AM Martinez, GI Webb
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 86-97, 2014
92014
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
92011
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
82016
Analyzing the impact of the discretization method when comparing Bayesian classifiers
MJ Flores, JA Gámez, AM Martínez, JM Puerta
International Conference on Industrial, Engineering and Other Applications …, 2010
82010
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
62019
MAP inference in dynamic hybrid Bayesian networks
D Ramos-López, AR Masegosa, AM Martínez, A Salmerón, TD Nielsen, ...
Progress in Artificial Intelligence 6 (2), 133-144, 2017
52017
The system can't perform the operation now. Try again later.
Articles 1–20