Ana M. Martínez

According to our database, Ana M. Martínez authored at least 24 papers between 2009 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2020

Analyzing concept drift: A case study in the financial sector.

Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón

Intell. Data Anal., 2020

2019

AMIDST: A Java toolbox for scalable probabilistic machine learning.

Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

Knowl. Based Syst., 2019

2017

Sample-Based Attribute Selective A<i>n</i> DE for Large Data.

Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb, Limin Wang

IEEE Trans. Knowl. Data Eng., 2017

MAP inference in dynamic hybrid Bayesian networks.

Darío Ramos-López, Andrés R. Masegosa, Ana M. Martínez, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Prog. Artif. Intell., 2017

Selective AnDE for large data learning: a low-bias memory constrained approach.

Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb, Limin Wang

Knowl. Inf. Syst., 2017

Scaling up Bayesian variational inference using distributed computing clusters.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Int. J. Approx. Reason., 2017

2016

Scalable Learning of Bayesian Network Classifiers.

Ana M. Martínez, Geoffrey I. Webb, Shenglei Chen, Nayyar Abbas Zaidi

J. Mach. Learn. Res., 2016

Probabilistic Graphical Models on Multi-Core CPUs Using Java 8.

Andrés R. Masegosa, Ana M. Martínez, Hanen Borchani

IEEE Comput. Intell. Mag., 2016

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.

Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

d-VMP: Distributed Variational Message Passing.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Financial Data Analysis with PGMs Using AMIDST.

Rafael Cabañas, Ana M. Martínez, Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.

Antonio Salmerón, Anders L. Madsen, Frank Jensen, Helge Langseth, Thomas D. Nielsen, Darío Ramos-López, Ana M. Martínez, Andrés R. Masegosa

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Dynamic Bayesian modeling for risk prediction in credit operations.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence, 2015

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Parallel Importance Sampling in Conditional Linear Gaussian Networks.

Antonio Salmerón, Darío Ramos-López, Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Antonio Fernández, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen

Proceedings of the Advances in Artificial Intelligence, 2015

2014

Domains of competence of the semi-naive Bayesian network classifiers.

M. Julia Flores, José A. Gámez, Ana M. Martínez

Inf. Sci., 2014

Highly Scalable Attribute Selection for Averaged One-Dependence Estimators.

Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2014

2012

Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers.

Ana M. Martínez, Geoffrey I. Webb, M. Julia Flores, José A. Gámez

Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

2011

Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter?

M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta

Appl. Intell., 2011

Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers.

M. Julia Flores, José A. Gámez, Ana M. Martínez, Antonio Salmerón

Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

2010

Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers.

M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta

Proceedings of the Trends in Applied Intelligent Systems, 2010

Towards a More Expressive Model for Dynamic Classification.

Shengtong Zhong, Ana M. Martínez, Thomas D. Nielsen, Helge Langseth

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009

GAODE and HAODE: two proposals based on AODE to deal with continuous variables.

M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

HODE: Hidden One-Dependence Estimator.

M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009