Publication list for Thomas D. Nielsen
- Davide Frazzetto, Bijay Neupane, Torben Bach Pedersen,
and Thomas Dyhre Nielsen.
Adaptive user-oriented direct load-control of residential flexible devices.
In ACM SIGCOMM e-Energy Conference 2018, United States, 6 2018.
Association for Computing Machinery.
(doi:10.1145/3208903.3208924)
- Tobias S. Jepsen, Christian Søndergaard Jensen,
Thomas Dyhre Nielsen, and Kristian Torp.
On network embedding for machine learning on road networks: A case study on the
danish road network.
In Proceedings of the 2018 IEEE International Conference on Big
Data, 2018.
- Andres Masegosa, Ana M. Martinez, Darío
Ramos-López, Rafael Cabanas de Paz, Antonio Salmerón, Helge
Langseth, Thomas Dyhre Nielsen, and Anders Læsø Madsen.
Amidst: A java toolbox for scalable probabilistic machine learning.
Knowledge-Based Systems, 2018.
(doi:doi.org/10.1016/j.knosys.2018.09.019)
- Darío Ramos-López, Andrés Masegosa, Antonio
Salmerón, Rafael Rumí, Helge Langseth, Thomas Dyhre Nielsen, and
Anders Læsø Madsen.
Scalable importance sampling estimation of gaussian mixture posteriors in
bayesian networks.
International Journal of Approximate Reasoning, 100:115–134,
2018.
(doi:10.1016/j.ijar.2018.06.004)
- Antonio Salmerón, Rafael Rumí, Helge Langseth,
Thomas Dyhre Nielsen, and Anders Læsø Madsen.
A review of inference algorithms for hybrid bayesian networks.
Journal of Artificial Intelligence Research, 62:799–828,
2018.
- Rafael Cabanas, Ana M. Martinez, Andres R. Masegosa,
Dario Ramos-Lopez, Antonio Sameron, Thomas D. Nielsen, Helge Langseth, and
Anders L. Madsen.
Financial data analysis with PGMs using AMIDST.
In Proceedings - 16th IEEE International Conference on Data Mining
Workshops, ICDMW 2016, pages 1284–1287, United States, 1 2017. IEEE.
(doi:10.1109/ICDMW.2016.0185)
- Anders Læsø Madsen, Frank Jensen, Antonio
Salmerón, Helge Langseth, and Thomas Dyhre Nielsen.
A parallel algorithm for Bayesian network structure learning from large data
sets.
Knowledge-Based Systems, 117:46–55, 2017.
(doi:10.1016/j.knosys.2016.07.031)
- Andrés
Masegosa, Thomas D. Nielsen, Helge Langseth, Daró Ramos-López, Antonio
Salmerón, and Anders L. Madsen.
Bayesian models of data streams with hierarchical power priors.
In Proceedings of the 34th International Conference on Machine Learning
(ICML), volume 70, pages 2334–2343, 2017.
- Andrés R. Masegosa, Ana M. Martinez, Helge
Langseth, Thomas Dyhre Nielsen, Antonio Salmerón, Darío
Ramos-López, and Anders Læsø Madsen.
Scaling up Bayesian variational inference using distributed computing
clusters.
International Journal of Approximate Reasoning, 88:435–451, 9
2017.
(doi:10.1016/j.ijar.2017.06.010)
- Darío Ramos-López, Andres Masegosa, Ana M.
Martinez, Antonio Salmerón, Thomas Dyhre Nielsen, Helge Langseth, and
Anders Læsø Madsen.
MAP inference in dynamic hybrid Bayesian networks.
Progress in Artificial Intelligence, 6(2):133–144, 2017.
(doi:10.1007/s13748-017-0115-7)
- Jacinto Arias,
José Gámez, Thomas Dyhre Nielsen, and José Puerta.
A
scalable pairwise class interaction framework for multidimensional
classification.
International Journal of Approximate Reasoning, 68:194–210, 2016.
(PDF, 310425 bytes)
- Finn V.
Jensen and Thomas Dyhre Nielsen.
Bayesian graphical models.
In Wiley StatsRef: Statistics Reference Online. John Wiley &
Sons, Ltd, 2016.
(doi:10.1002/9781118445112.stat07360.pub2)
- Manuel Luque,
Thomas Dyhre Nielsen, and Finn V. Jensen.
Anytime decision making based on unconstrained influence diagram.
International journal of intelligent systems, 31:379–298, 2016.
(PDF, 334602 bytes)
(doi:10.1002/int.21780)
- Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen,
Kim G. Larsen, and Brian Nielsen.
Learning deterministic probabilistic automata from a model checking
perspective.
Machine Learning, 105(2):255–299, 2016.
(doi:10.1007/s10994-016-5565-9)
- Andres Masegosa, Ana M. Martinez, Helge Langseth,
Thomas Dyhre Nielsen, Antonio Salmerón, Darío Ramos-López, and
Anders Læsø Madsen.
d-VMP: Distributed variational message passing.
In PGM: JMLR Workshop and Conference Proceedings, pages 321–332,
2016.
- Andres Masegosa, Ana Maria Martinez, Darío
Ramos-López, Helge Langseth, Thomas Dyhre Nielsen, Antonio
Salmerón, Rafael Cabanas, and Anders Læsø Madsen.
A Java toolbox for analysis of massive
data streams using probabilistic graphical models.
2016.
European Data Forum 2016.
- Darío Ramos-López, Antonio Salmerón, Rafael
Rumí, Ana M. Martinez, Thomas Dyhre Nielsen, Andres Masegosa, Helge
Langseth, and Anders Læsø Madsen.
Scalable MAP inference in Bayesian networks based on a map-reduce approach.
In PGM: JMLR Workshop and Conference Proceedings, pages 415–425,
2016.
- Antonio Salmerón, Anders Læsø Madsen, Frank
Jensen, Helge Langseth, Thomas Dyhre Nielsen, Darío Ramos-López,
Ana M. Martinez, and Andres Masegosa.
Parallel filter-based feature selection based on balanced incomplete block
designs.
In ECAI 2016, pages 743–750. IOS Press, 2016.
(doi:10.3233/978-1-61499-672-9-743)
- Hanen
Borchani, Ana M. Martínez, Andrés Masegosa, Helge Langseth, Thomas D.
Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, and
Ramón Sáez.
Dynamic Bayesian modeling for risk prediction in credit operations.
In Proceedings of the Thirteenth Scandinavian Conference on Artificial
Intelligence, 2015.
(PDF, 341508 bytes)
- Hanen
Borchani, Ana M. Martínez, Andrés Masegosa, Helge Langseth, Thomas D.
Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, and
Ramón Sáez.
Modeling concept drift: A probabilistic graphical model based approach.
In Proceedings of the Fourteenth International Symposium on Intelligent
Data Analysis (IDA'15), pages 72–83, 2015.
(PDF, 376596 bytes)
- Hanen Borchani, Ana Maria Martinez, Andres Masegosa,
Helge Langseth, Thomas Dyhre Nielsen, Antonio Salmerón, Antonio
Fernández, Anders Læsø Madsen, and Ramón Sáez.
Dynamic Bayesian modeling for risk prediction in credit operations.
In The 13th Scandinavian Conference on Artificial Intelligence
(SCAI2015), pages 17–26. IOS Press, 2015.
(doi:10.3233/978-1-61499-589-0-17)
- Helge Langseth and Thomas Dyhre Nielsen.
Scalable learning of probabilistic latent models for collaborative filtering.
Decision Support Systems, 74:1–11, 2015.
(PDF, 269228 bytes)
(doi:10.1016/j.dss.2015.03.006)
- Anders Læsø Madsen, Frank Jensen, Antonio
Salmerón, Helge Langseth, and Thomas Dyhre Nielsen.
Parallelisation of the PC algorithm.
In Advances in Artificial Intelligence (CAEPIA), pages 14–24,
Germany, 2015. Springer.
(doi:10.1007/978-3-319-24598-0_2)
- Andres Masegosa, Ana Maria Martinez, Hanen Borchani,
Darío Ramos-López, Thomas Dyhre Nielsen, Helge Langseth, Antonio
Salmerón, and Anders Læsø Madsen.
Amidst: Analysis of massive data streams.
In The 27th Benelux Conference on Artificial Intelligence (BNAIC
2015), 10 2015.
- Antonio Salmerón, Darío Ramos-López, Hanen
Borchani, Ana Maria Martinez, Andres R. Masegosa, Antonio Fernández,
Helge Langseth, Anders Læsø Madsen, and Thomas Dyhre Nielsen.
Parallel importance sampling in conditional linear Gaussian networks.
In José M. Puerta, José A. Gámez, Bernabe Dorronsoro, Edurne
Barrenechea, Alicia Troncoso, Bruno Baruque, and Mikel Galar, editors,
Advances in Artificial Intelligence (CAEPIA), pages 36–46,
Germany, 2015. Springer.
(doi:10.1007/978-3-319-24598-0_4)
- Antonio Salmerón, Rafael Rumí, Helge Langseth,
Anders Læsø Madsen, and Thomas Dyhre Nielsen.
MPE inference in conditional linear Gaussian networks.
In Sébastien Destercke and Thierry Denoeux, editors, Symbolic and
Quantitative Approaches to Reasoning with Uncertainty, pages 407–416,
Germany, 2015. Springer.
(doi:10.1007/978-3-319-20807-7_37)
- Gherardo
Varando, Pedro L. López-Cruz, Thomas Dyhre Nielsen, Concha Bielza, and
Pedro Larrañga.
Conditional density approximations with mixtures of polynomials.
International Journal of Intelligent Systems, 3:236–264, 2015.
(PDF, 1142688 bytes)
- Jacinto Arias,
José Gámez, Thomas Dyhre Nielsen, and José Puerta.
A pairwise class interaction framework for multilabel classification.
In Linda van der Gaag and Ad Feelders, editors, Proceedings of European
Workshop on Probabilistic Graphical Models, volume 8754 of
Lecture Notes in Computer Science, pages 17–32. Springer
International Publishing, 2014.
(doi:10.1007/978-3-319-11433-0_2)
- Helge
Langseth, Thomas D. Nielsen, Inmaculada Pérez-Bernabé, and Antonio
Salmerón.
Learning mixtures of truncated basis functions from data.
International Journal of Approximate Reasoning, 55(4):940–956,
2014.
(PDF, 782084 bytes)
(doi:10.1016/j.ijar.2013.09.012)
- Anders L. Madsen, Frank Jensen, Antonio Salmerón, Martin Karlsen, Helge Langseth,
and Thomas Dyhre Nielsen.
A new method for vertical parallelisation of TAN learning based on balanced
incomplete block designs.
In Linda van der Gaag and Ad Feelders, editors, Proceedings of European
Workshop on Probabilistic Graphical Models, volume 8754 of
Lecture Notes in Computer Science, pages 302–317. Springer
International Publishing, 2014.
(doi:10.1007/978-3-319-11433-0_20)
- Shengtong Zhong,
Helge Langseth, and Thomas Dyhre Nielsen.
A classification-based approach to monitoring the safety of dynamic systems.
Reliability Engineering and System Safety, 121:61–71, 2014.
(PDF, 1126619 bytes)
(doi:10.1016/j.ress.2013.07.016)
- Finn V.
Jensen and Thomas Dyhre Nielsen.
Probabilistic decision graphs for optimization under uncertainty.
Annals of Operations Research, 204:223–248, 2013.
Surveys in Operations Research III (Invited Surveys from /4OR/, 2009-2011).
(PDF, 298773 bytes)
- Pedro L.
López-Cruz, Thomas Dyhre Nielsen, Concha Bielza, and Pedro Larrañga.
Learning mixtures of polynomials of conditional densities from data.
In Conference of the Spanish Association for Artificial
Intelligence, pages 363 – 372, 2013.
(PDF, 598110 bytes)
- Yingke Chen
and Thomas Dyhre Nielsen.
Active learning of Markov decision processes for system verification.
In International Conference on Machine Learning and Applications
(ICMLA), pages 289–294, 2012.
(PDF, 388326 bytes)
(doi:10.1109/ICMLA.2012.158)
- Yingke Chen, Hua
Mao, Manfred Jaeger, Thomas Dyhre Nielsen, Kim G. Larsen, and Brain Nielsen.
Learning Markov models for stationary system behaviors.
In NASA Formal Methods Symposium (NFM), pages 216 – 230, 2012.
(PDF, 381625 bytes)
- Helge Langseth and Thomas Dyhre Nielsen.
A latent model for collaborative filtering.
International Journal of Approximate Reasoning, 53(4):447–466,
June 2012.
(PDF, 5125622 bytes)
(doi:10.1016/j.ijar.2011.11.002)
- Helge
Langseth, Thomas D. Nielsen, Rafael Rumí, and Antonio Salmerón.
Inference in hybrid Bayesian networks with mixtures of truncated basis
functions.
In Andrés Cano, Manuel Gómez-Olmedo, and Thomas Dyhre Nielsen, editors,
Proceedings of the Sixth European Workshop on Probabilistic Graphical
Models, pages 171–178, 2012.
(PostScript, 8 pages, 538706 bytes)
(PDF, 125559 bytes)
- Helge
Langseth, Thomas D. Nielsen, and Antonio Salmerón.
Learning mixtures of truncated basis functions from data.
In Andrés Cano, Manuel Gómez-Olmedo, and Thomas Dyhre Nielsen, editors,
Proceedings of the Sixth European Workshop on Probabilistic Graphical
Models, pages 163–170, 2012.
MATLAB-source.zip.
(PDF, 443431 bytes)
- Hua Mao, Yingke
Chen, Manfred Jaeger, Thomas Dyhre Nielsen, Kim G. Larsen, and Brain Nielsen.
Learning Markov decision processes for model checking.
In Workshop on Quantities in Formal Methods (QFM), volume 103,
pages 49 –63, 2012.
- Finn V.
Jensen and Thomas Dyhre Nielsen.
Probabilistic decision graphs for optimization under uncertainty.
4OR - Quarterly Journal of Operations Research, 9(1):1–28, 2011.
(PDF, 298163 bytes)
(doi:10.1007/s10288-011-0159-7)
- Helge
Langseth, Thomas Dyhre Nielsen, Rafael Rumí, and Antonio Salmerón.
Mixtures of truncated basis functions.
International Journal of Approximate Reasoning, 53(2):212–227,
2011.
MATLAB-source.zip.
(PDF, 459054 bytes)
(doi:10.1016/j.ijar.2011.10.004)
- Hua Mao, Yingke Chen,
Manfred Jaeger, Thomas Dyhre Nielsen, Kim G. Larsen, and Brain Nielsen.
Learning probabilistic automata for model checking.
In 8th International conference on quantitative evaluation of systems
(QEST), pages 111–120, 2011.
(PostScript, 10 pages, 620573 bytes)
(PDF, 197739 bytes)
- Antonio
Fernández, Helge Langseth, Thomas Dyhre Nielsen, and Antonio Salmerón.
Parameter learning in MTE networks using incomplete data.
In Petri Myllymäki, Teemu Roos, and Tommi Jaakkola, editors,
Proceedings of the Fifth European Workshop on Probabilistic Graphical
Models, pages 137–144, 2010.
(PostScript, 8 pages, 679698 bytes)
(PDF, 154783 bytes)
- Manfred
Jaeger and Thomas Dyhre Nielsen (eds.).
Message from the guest editors.
International Journal of Approximate Reasoning - Special Issue on
PGM-2008, 51:473, 2010.
Available online 11 February 2010.
(doi:10.1016/j.ijar.2010.01.006)
- Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí, and
Antonio Salmerón.
Parameter estimation and model selection for mixtures of truncated
exponentials.
International Journal of Approximate Reasoning, 51:485–498, 2010.
(PostScript, 22 pages, 703668 bytes)
(PDF, 289581 bytes)
(doi:10.1016/j.ijar.2010.01.008)
- Shengtong Zhong,
Ana M. Martínez, Thomas Dyhre Nielsen, and Helge Langseth.
Towards a more expressive model for dynamic classification.
In Proceedings of the Twentythird International Florida Artificial
Intelligence Research Symposium Conference, 2010.
- Kristian S. Ahlmann-Ohlsen, Finn V. Jensen, Thomas Dyhre
Nielsen, Ole Pedersen, and Marta Vomlelová.
A comparison of two approaches for solving unconstrained influence diagrams.
International Journal of Approximate Reasoning, 50(1):153–173,
2009.
(PostScript, 36 pages, 850833 bytes)
(PDF, 346301 bytes)
(doi:10.1016/j.ijar.2008.08.001)
- Helge Langseth and Thomas Dyhre Nielsen.
Latent classification models for binary data.
Pattern Recognition, 42(11):2724 – 2736, 2009.
More
information.
(PostScript, 33 pages, 2422974 bytes)
(PDF, 327865 bytes)
(doi:10.1016/j.patcog.2009.05.002)
- Helge Langseth and Thomas Dyhre Nielsen.
A latent model for collaborative filtering.
Technical Report 09-003, Aalborg university, Denmark, 2009.
(PostScript, 25 pages, 524748 bytes)
(PDF, 242171 bytes)
- Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí,
and Antonio Salmerón.
Inference in hybrid Bayesian networks.
Reliability Engineering & System Safety, 94(10):1499 – 1509,
2009.
(PostScript, 29 pages, 1237096 bytes)
(PDF, 425936 bytes)
(doi:10.1016/j.ress.2009.02.027)
- Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí,
and Antonio Salmerón.
Maximum likelihood learning of conditional MTE distributions.
In Proceedings of the Tenth European Conference on Symbolic and
Quantitative Approaches to Reasoning with Uncertainty, pages 240–251,
2009.
(PostScript, 12 pages, 1411761 bytes)
(PDF, 304257 bytes)
- José A.
Gámez, Juan L. Mateo, Thomas Dyhre Nielsen, and José M. Puerta.
Robust classification using mixtures of dependency networks.
In Manfred Jaeger and Thomas D. Nielsen, editors, Proceedings of the
Fourth European Workshop on Probabilistic Graphical Models, pages
129–136, 2008.
(PostScript, 8 pages, 327115 bytes)
(PDF, 147173 bytes)
- Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí, and
Antonio Salmerón.
Parameter estimation in mixtures of truncated exponentials.
In Manfred Jaeger and Thomas D. Nielsen, editors, Proceedings of the
Fourth European Workshop on Probabilistic Graphical Models, pages
169–176, 2008.
(PostScript, 8 pages, 422449 bytes)
(PDF, 159878 bytes)
- Manuel
Luque, Thomas Dyhre Nielsen, and Finn V. Jensen.
An anytime algorithm for evaluating unconstrained influence diagrams.
In Manfred Jaeger and Thomas D. Nielsen, editors, Proceedings of the
Fourth European Workshop on Probabilistic Graphical Models, pages
177–184, 2008.
(PostScript, 8 pages, 322730 bytes)
(PDF, 137468 bytes)
- Søren Holbech Nielsen and Thomas Dyhre Nielsen.
Adapting Bayes network structures to non-stationary domains.
International Journal of Approximate Reasoning, 49(2):379–397,
2008.
(PostScript, 23 pages, 676725 bytes)
(PDF, 289996 bytes)
(doi:10.1016/j.ijar.2008.02.007)
- Finn V.
Jensen and Thomas Dyhre Nielsen.
Bayesian Networks and Decision
Graphs.
Springer-Verlag New York, Inc., second edition, 2007.
463 pages.
- Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí, and
Antonio Salmerón.
Maximum likelihood vs. least squares for estimating mixtures of truncated
exponentials.
Presented at INFORMS 2007 by Antonio Salmeron, 2007.
(PDF, 3696032 bytes)
- Thomas Dyhre Nielsen and Finn V. Jensen.
On-line alert systems for production plants: A conflict based approach.
International Journal of Approximate Reasoning, 45(2):255–270,
2007.
(PDF, 555018 bytes)
(doi:10.1016/j.ijar.2006.06.010)
- Søren Holbech Nielsen and Thomas Dyhre Nielsen.
Adapting Bayes network structures to non-stationary domains.
Technical report, Department of Computer Science, Aalborg University, Fredrik
Bajers 7C, 9220 Aalborg, Denmark, 2007.
(PostScript, 45 pages, 898329 bytes)
(PDF, 426054 bytes)
- Søren Holbech Nielsen, Thomas Dyhre Nielsen, and Finn V.
Jensen.
Multi-currency
influence diagrams.
213:275–294, 2007.
(PostScript, 21 pages, 2555389 bytes)
(PDF, 555827 bytes)
- Jens Alsted Hansen, Thomas Dyhre Nielsen, and Henrik
Shiøler.
A COTS framework for sensor fusion using dynamic Bayesian networks in
livestock production.
In Prooceedings of the Nineteenth International Conference on Computer
Applications in Industry and Engineering, pages 41–48, 2006.
- Jens Alsted Hansen, Thomas Dyhre Nielsen, and Henrik
Shiøler.
Monitoring indoor temperature and humidity for pig stables.
In Adjunct Proceedings of the 3rd European Workshop on Wireless Sensor
Networks, pages 24–26, 2006.
- Jens Alsted Hansen, Thomas Dyhre Nielsen, and Henrik
Shiøler.
Sensor fusion using dynamic Bayesian networks in livestock production
buildings.
In International Conference on Computational Intelligence for Modelling
Control and Automation, 2006.
- Finn V. Jensen, Thomas Dyhre Nielsen, and Prakash P.
Shenoy.
Sequential influence diagrams: A unified asymmetry framework.
International Journal of Approximate Reasoning, 42(1–2):101–118,
2006.
(PDF, 243960 bytes)
(doi:10.1016/j.ijar.2005.10.007)
- Helge Langseth and Thomas Dyhre Nielsen.
Classification using hierarchical naive Bayes models.
Machine Learning, 63(2):135–159, 2006.
(PDF, 334132 bytes)
(doi:10.1007/s10994-006-6136-2)
- Thomas Dyhre Nielsen and Jean-Yves Jaffray.
Dynamic decision making without expected utility: an operational approach.
European Journal of Operational Research, 169(1):226–246, 2006.
Published online on September 11th, 2004.
(PDF, 287480 bytes)
(doi:sd/article/S0377221704004229)
- Søren Holbech Nielsen and Thomas Dyhre Nielsen.
Adapting Bayes network structures to non-stationary domains.
In Proceedings of the Third European Workshop on Probabilistic Graphical
Models, pages 223–230, 2006.
(PDF, 117107 bytes)
- Helge Langseth and Thomas Dyhre Nielsen.
Latent classification models.
Machine Learning Journal – Special Issue on Probabilistic Graphical
Models for Classification, 59(3):237–265, 2005.
(PDF, 2906277 bytes)
(doi:10.1007/s10994-005-0472-5)
- Thomas Dyhre Nielsen and Nevin L. Zhang (eds.).
Message from the guest editors.
International Journal of Approximate Reasoning - Selected papers from
ECSQARU 2003, 38(3):215–216, 2005.
Available online 17 September 2004.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Alert systems for production plants: A methodology based on conflict analysis.
In Lluís Godo, editor, Proceedings of the Eighth European Conference
on Symbolic and Quantitative Approaches to Reasoning with Uncertainty,
number 3571 in Lecture Notes in Artificial Intelligence, pages 76–87.
Springer-Verlag, 2005.
(PDF, 301082 bytes)
(doi:10.1007/11518655_8)
- Finn V. Jensen, Thomas Dyhre Nielsen, and Prakash P.
Shenoy.
Sequential influence diagrams: A unified asymmetry framework.
In Peter Lucas, editor, Proceedings of the Second European Workshop on
Probabilistic Graphical Models, pages 121–128, 2004.
(PostScript, 8 pages, 326221 bytes)
- Thomas Dyhre Nielsen and Finn V. Jensen.
Advances
in decision graphs.
In José Gámez, Serafí Moral, and Antonio Salmerón, editors,
Advances in Bayesian networks, volume 146 of Studies in
Fuzziness and Soft Computing, pages 137–159. Springer-Verlag,
2004.
(PDF, 250003 bytes)
- Thomas Dyhre Nielsen and Finn V. Jensen.
Learning a
decision maker's utility function from (possibly) inconsistent behavior.
Artificial Intelligence, 160:53–78, 2004.
(PDF, 331656 bytes)
- Søren Holbech Nielsen, Thomas Dyhre Nielsen, and Finn V.
Jensen.
Multi-currency influence diagrams.
In Peter Lucas, editor, Proceedings of the Second European Workshop on
Probabilistic Graphical Models, pages 153–160, 2004.
(PDF, 161035 bytes)
- Nevin L.
Zhang, Thomas Dyhre Nielsen, and Finn V. Jensen.
Latent
variable discovery in classification models.
Artificial Intelligence in Medicine, 30(3):283–299, 2004.
- Helge Langseth and Thomas Dyhre Nielsen.
Fusion of domain knowledge with data for structural learning in object oriented
domains.
Journal of Machine Learning Research, Special issue on the
Fusion of Domain Knowledge with Data for Decision Support,
4:339–368, 2003.
(PDF, 256291 bytes)
- Thomas Dyhre Nielsen and Nevin L. Zhang (eds.).
Proceedings
of the Seventh European Conference on Symbolic and Quantitative
Approaches to Reasonng with Uncertainty.
Number 2711 in Lecture Notes in Artificial Intelligence. Springer-Verlag,
2003.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Representing
and solving asymmetric decision problems.
International Journal of Information Technology and Decision
Making, 2(2):217–263, 2003.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Sensitivity analysis in influence diagrams.
IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems
and Humans, 33(2):223–234, 2003.
- Helge Langseth and Thomas Dyhre Nielsen.
Classification using hierarchical naïve Bayes models.
Technical Report R-02-004, Department of Computer Science, Fredrik Bajers 7E,
9220 Aalborg, Denmark, 2002.
(PostScript, 19 pages, 410783 bytes)
- Thomas Dyhre Nielsen.
Decomposition
of influence diagrams.
Journal of Applied Non-Classical Logics – Symbolic and
Quantitative Approaches to Reasoning with Uncertainty,
12(2):135–150, 2002.
Extended version of the conference paper.
- Olav Bangsø, Helge Langseth, and Thomas Dyhre Nielsen.
Structural learning in object oriented domains.
In Ingrid Russel and John Kolen, editors, Proceedings of the Fourteenth
International Florida Artificial Intelligence Research Symposium
Conference, pages 340–344, 2001.
(PostScript, 5 pages, 190602 bytes)
- Thomas Dyhre Nielsen.
Decomposition
of influence diagrams.
In Salem Benferhat and Philippe Besnard, editors, Proceedings of the
Sixth European Conference on Symbolic and Quantitative Approaches to
Reasoning with Uncertainty, number 2143 in Lecture Notes in Artificial
Intelligence, pages 144–155. Springer-Verlag, 2001.
- Thomas Dyhre Nielsen.
Graphical models for partially sequential decision problems.
PhD thesis, Aalborg University, Department of Computer Science, Fredrik Bajers
7E, 9220 Aalborg, Denmark, 2001.
(Gzipped PostScript, 209 pages, 556178 bytes)
- Thomas Dyhre Nielsen and Jean-Yves Jaffray.
An operational approach to rational decision making based on rank dependent
utility.
Technical Report R-01-5001, Department of Computer Science, Fredrik Bajers 7E,
9220 Aalborg, Denmark, 2001.
(PDF, 305722 bytes)
- Thomas Dyhre Nielsen and Finn V. Jensen.
Cutting influence diagrams down to the core.
In Proceedings of the Seventh Scandinavian Conference on Artificial
Intelligence, pages 159–160, 2001.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Well-defined decision scenarios.
Technical Report R-01-5002, Department of Computer Science, Fredrik Bajers 7E,
9220 Aalborg, Denmark, 2001.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Representing and solving asymmetric Bayesian decision problems.
In Craig Boutilier and Moisés Goldszmidt, editors, Proceedings of the
Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI),
pages 416–425. Morgan Kaufmann Publishers, 2000.
(PostScript, 10 pages, 254610 bytes)
- Thomas Dyhre Nielsen, Pierre-Henri Wuillemin, Finn V.
Jensen, and Uffe Kjærulff.
Using ROBDDs for inference in Bayesin networks with troubleshooting as an
example.
In Craig Boutilier and Moisés Goldszmidt, editors, Proceedings of the
Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI),
pages 426–435. Morgan Kaufmann Publishers, 2000.
(PostScript, 10 pages, 396045 bytes)
- Thomas Dyhre Nielsen and Finn V. Jensen.
Representing and solving asymmetric Bayesian decision problems.
Technical report, Department of Computer Science, Fredrik Bajers 7C, 9220
Aalborg, Denmark, 1999.
R-99-5010.
- Thomas Dyhre Nielsen and Finn V. Jensen.
Well-defined decision scenarios.
In Kathryn B. Laskey and Henri Prade, editors, Proceedings of the
Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI),
pages 502–511. Morgan Kaufmann Publishers, 1999.
(PostScript, 10 pages, 396710 bytes)