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ORCIDHanen Borchani
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Books and Theses
- 2013
[b1]Hanen Borchani:
Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data. Technical University of Madrid, Spain, 2013
Journal Articles
- 2016
- [j7]Andrés R. Masegosa, Ana M. Martínez
, Hanen Borchani:
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8. IEEE Comput. Intell. Mag. 11(2): 41-54 (2016) - [j6]Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza:
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. 20(2): 257-280 (2016) - 2015
- [j5]Hanen Borchani, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A survey on multi-output regression. WIREs Data Mining Knowl. Discov. 5(5): 216-233 (2015) - 2013
- [j4]Hanen Borchani, Concha Bielza, Carlos Toro, Pedro Larrañaga:
Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artif. Intell. Medicine 57(3): 219-229 (2013) - 2012
- [j3]Hanen Borchani, Concha Bielza, Pablo Martínez-Martín, Pedro Larrañaga:
Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). J. Biomed. Informatics 45(6): 1175-1184 (2012) - 2011
- [j2]Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Classifying evolving data streams with partially labeled data. Intell. Data Anal. 15(5): 655-670 (2011) - 2008
- [j1]Hanen Borchani, Nahla Ben Amor, Fédia Khalfallah:
Learning and Evaluating Bayesian Network Equivalence Classes from Incomplete Data. Int. J. Pattern Recognit. Artif. Intell. 22(2): 253-278 (2008)
Conference and Workshop Papers
- 2019
- [c7]Hanen Borchani, Wojciech Michal Pawlak, Steffen Holmslykke, Allan Peter Engsig-Karup:
Data-driven American Option Pricing using Artificial Neural Networks. ICDM (Posters) 2019: 168-172 - 2015
- [c6]Antonio Salmerón, Darío Ramos-López, Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Antonio Fernández, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen:
Parallel Importance Sampling in Conditional Linear Gaussian Networks. CAEPIA 2015: 36-46 - [c5]Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez:
Modeling Concept Drift: A Probabilistic Graphical Model Based Approach. IDA 2015: 72-83 - [c4]Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez:
Dynamic Bayesian modeling for risk prediction in credit operations. SCAI 2015: 17-26 - 2010
- [c3]Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Mining Concept-Drifting Data Streams Containing Labeled and Unlabeled Instances. IEA/AIE (1) 2010: 531-540 - 2007
- [c2]Hanen Borchani, Maher Chaouachi, Nahla Ben Amor:
Learning Causal Bayesian Networks from Incomplete Observational Data and Interventions. ECSQARU 2007: 17-29 - 2006
- [c1]Hanen Borchani, Nahla Ben Amor, Khaled Mellouli:
Learning Bayesian Network Equivalence Classes from Incomplete Data. Discovery Science 2006: 291-295
Informal and Other Publications
- 2016
- [i1]Andrés R. Masegosa, Ana M. Martínez, Hanen Borchani:
Probabilistic Graphical Models on Multi-Core CPUs using Java 8. CoRR abs/1604.07990 (2016)
Coauthor Index
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