Ana M. Martínez

26 papers A* 1A 1B 1C 2Misc 1Journal 12Unranked 8
YearRankTypeTitle / Venue / Authors
2020 J jnl
Analyzing concept drift: A case study in the financial sector.
Intell. Data Anal.
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón
2019 J jnl
AMIDST: A Java toolbox for scalable probabilistic machine learning.
Knowl. Based Syst.
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen
2017 J jnl
AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning.
CoRR
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
2017 J jnl
MAP inference in dynamic hybrid Bayesian networks.
Prog. Artif. Intell.
Darío Ramos-López, Andrés R. Masegosa, Ana M. Martínez, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
2017 J jnl
Sample-Based Attribute Selective A
IEEE Trans. Knowl. Data Eng.
Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb, Limin Wang
2017 J jnl
Scaling up Bayesian variational inference using distributed computing clusters.
Int. J. Approx. Reason.
Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen
2017 J jnl
Selective AnDE for large data learning: a low-bias memory constrained approach.
Knowl. Inf. Syst.
Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb, Limin Wang
2016 — conf
Financial Data Analysis with PGMs Using AMIDST.
ICDM Workshops
Rafael Cabañas, Ana M. Martínez, Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
2016 A conf
Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.
ECAI
Antonio Salmerón, Anders L. Madsen, Frank Jensen, Helge Langseth, Thomas D. Nielsen, Darío Ramos-López, Ana M. Martínez, Andrés R. Masegosa
2016 J jnl
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8.
IEEE Comput. Intell. Mag.
Andrés R. Masegosa, Ana M. Martínez, Hanen Borchani
2016 J jnl
Probabilistic Graphical Models on Multi-Core CPUs using Java 8.
CoRR
Andrés R. Masegosa, Ana M. Martínez, Hanen Borchani
2016 J jnl
Scalable Learning of Bayesian Network Classifiers.
J. Mach. Learn. Res.
Ana M. Martínez, Geoffrey I. Webb, Shenglei Chen, Nayyar Abbas Zaidi
2016 — conf
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.
Probabilistic Graphical Models
Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen
2016 — conf
d-VMP: Distributed Variational Message Passing.
Probabilistic Graphical Models
Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen
2015 — conf
Dynamic Bayesian modeling for risk prediction in credit operations.
SCAI
Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez
2015 B conf
Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.
IDA
Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez
2015 — conf
Parallel Importance Sampling in Conditional Linear Gaussian Networks.
CAEPIA
Antonio Salmerón, Darío Ramos-López, Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Antonio Fernández, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen
2014 J jnl
Domains of competence of the semi-naive Bayesian network classifiers.
Inf. Sci.
M. Julia Flores, José A. Gámez, Ana M. Martínez
2014 — conf
Highly Scalable Attribute Selection for Averaged One-Dependence Estimators.
PAKDD (2)
Shenglei Chen, Ana M. Martínez, Geoffrey I. Webb
2012 — conf
Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers.
HAIS (2)
Ana M. Martínez, Geoffrey I. Webb, M. Julia Flores, José A. Gámez
2011 J jnl
Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter?
Appl. Intell.
M. Julia Flores, José A. Gámez, Ana M. Martínez, José M. Puerta
2011 C conf
Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers.
ISDA
M. Julia Flores, José A. Gámez, Ana M. Martínez, Antonio Salmerón
2010 — conf
Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers.
IEA/AIE (1)
M. Julia Flores, José A. Gámez, Ana M. Martínez, José M. Puerta
2010 Misc conf
Towards a More Expressive Model for Dynamic Classification.
FLAIRS
Shengtong Zhong, Ana M. Martínez, Thomas D. Nielsen, Helge Langseth
2009 A* conf
GAODE and HAODE: two proposals based on AODE to deal with continuous variables.
ICML
M. Julia Flores, José A. Gámez, Ana M. Martínez, José M. Puerta
2009 C conf
HODE: Hidden One-Dependence Estimator.
ECSQARU
M. Julia Flores, José A. Gámez, Ana M. Martínez, José M. Puerta