Thomas Dyhre Nielsen

  • Selma Lagerløfs Vej 300, 1-2-34

    9220 Aalborg Ø

    Denmark

  • Selma Lagerlöfs Vej 300, Cassiopeia

    9220 Aalborg

    Denmark

19972019
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Research Output 1999 2019

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Journal article
2019
1 Citation (Scopus)

AMIDST: A Java toolbox for scalable probabilistic machine learning

Masegosa, A., Martinez, A. M., Ramos-López, D., Cabanas de Paz, R., Salmerón, A., Langseth, H., Nielsen, T. D. & Madsen, A. L., 1 Jan 2019, In : Knowledge-Based Systems. 163, p. 595-597 3 p.

Research output: Contribution to journalJournal articleResearchpeer-review

Learning systems
Message passing
Probability distributions
Java
Machine learning

Prescriptive Analytics: A Survey of Emerging Trends And Technologies

Frazzetto, D., Nielsen, T. D., Pedersen, T. B. & Siksnys, L., 1 Aug 2019, In : V L D B Journal. 24 p.

Research output: Contribution to journalJournal articleResearchpeer-review

2018
2 Citations (Scopus)

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks

Ramos-López, D., Masegosa, A., Salmerón, A., Rumí, R., Langseth, H., Nielsen, T. D. & Madsen, A. L., 1 Sep 2018, In : International Journal of Approximate Reasoning. 100, p. 115-134 20 p., 100.

Research output: Contribution to journalJournal articleResearchpeer-review

Importance sampling
Gaussian Mixture
Importance Sampling
Bayesian networks
Bayesian Networks
2017
18 Citations (Scopus)
67 Downloads (Pure)

A parallel algorithm for Bayesian network structure learning from large data sets

Madsen, A. L., Jensen, F., Salmerón, A., Langseth, H. & Nielsen, T. D., 2017, In : Knowledge-Based Systems. 117, p. 46-55

Research output: Contribution to journalJournal articleResearchpeer-review

Open Access
File
2 Citations (Scopus)
62 Downloads (Pure)

MAP inference in dynamic hybrid Bayesian networks

Ramos-López, D., Masegosa, A., Martinez, A. M., Salmerón, A., Nielsen, T. D., Langseth, H. & Madsen, A. L., 2017, In : Progress in Artificial Intelligence. 6, 2, p. 133–144 12 p.

Research output: Contribution to journalJournal articleResearchpeer-review

Open Access
File
7 Citations (Scopus)

Scaling up Bayesian variational inference using distributed computing clusters

Masegosa, A. R., Martinez, A. M., Langseth, H., Nielsen, T. D., Salmerón, A., Ramos-López, D. & Madsen, A. L., 1 Sep 2017, In : International Journal of Approximate Reasoning. 88, p. 435-451 17 p.

Research output: Contribution to journalJournal articleResearchpeer-review

Distributed computer systems
Distributed Computing
Variational Methods
Variational Bayes
Scaling
2016
1 Citation (Scopus)
246 Downloads (Pure)

Anytime decision making based on unconstrained influence diagrams

Luque, M., Nielsen, T. D. & Jensen, F. V., 2016, In : International Journal of Intelligent Systems. 31, 4, p. 379-398 20 p.

Research output: Contribution to journalJournal articleResearchpeer-review

File
Influence Diagrams
Decision making
Decision Making
Optimal Policy
Temporal Constraints
4 Citations (Scopus)

A scalable pairwise class interaction framework for multidimensional classification

Arias, J., Gámez, J. A., Nielsen, T. D. & Puerta, J. M., 2016, In : International Journal of Approximate Reasoning. 68, p. 194–210

Research output: Contribution to journalJournal articleResearchpeer-review

Pairwise
Classifiers
Interaction
Scalability
Classifier
12 Citations (Scopus)
211 Downloads (Pure)

Learning deterministic probabilistic automata from a model checking perspective

Mao, H., Chen, Y., Jaeger, M., Nielsen, T. D., Larsen, K. G. & Nielsen, B., 2016, In : Machine Learning. 105, 2, p. 255-299 45 p.

Research output: Contribution to journalJournal articleResearchpeer-review

File
Model checking
Learning algorithms
Temporal logic
Hardware
2015
3 Citations (Scopus)
107 Downloads (Pure)

Conditional Density Approximations with Mixtures of Polynomials

Varando, G., López-Cruz, P. L., Nielsen, T. D., Bielza, C. & Larrañga, P., 2015, In : International Journal of Intelligent Systems. 30, 3, p. 236-264

Research output: Contribution to journalJournal articleResearchpeer-review

File
Conditional Density
Polynomials
Polynomial
Approximation
Basis Functions
9 Citations (Scopus)
241 Downloads (Pure)

Scalable learning of probabilistic latent models for collaborative filtering

Langseth, H. & Nielsen, T. D., 2015, In : Decision Support Systems. 74

Research output: Contribution to journalJournal articleResearchpeer-review

File
Collaborative filtering
Statistical Models
Learning
Self-Help Groups
Scalability
2014
4 Citations (Scopus)
917 Downloads (Pure)

A classification-based approach to monitoring the safety of dynamic systems

Zhong, S., Langseth, H. & Nielsen, T. D., Jan 2014, In : Reliability Engineering & System Safety. 121, p. 61-71

Research output: Contribution to journalJournal articleResearchpeer-review

File
Dynamical systems
Monitoring
Sensors
Experiments
20 Citations (Scopus)
306 Downloads (Pure)

Learning Mixtures of Truncated Basis Functions from Data

Langseth, H., Nielsen, T. D., Pérez-Bernabé, I. & Salmerón, A., 2014, In : International Journal of Approximate Reasoning. 55, 4, p. 940-966

Research output: Contribution to journalJournal articleResearchpeer-review

File
Basis Functions
Bandwidth
Convex optimization
Bayesian networks
Distribution functions
2013
4 Citations (Scopus)
455 Downloads (Pure)

Probabilistic decision graphs for optimization under uncertainty

Jensen, F. V. & Nielsen, T. D., Apr 2013, In : Annals of Operations Research. 204, 1, p. 223-248

Research output: Contribution to journalJournal articleResearchpeer-review

File
Uncertainty
Graph
Influence diagrams
Modeling
Language
2012
27 Citations (Scopus)
876 Downloads (Pure)

A latent model for collaborative filtering

Langseth, H. & Nielsen, T. D., Jun 2012, In : International Journal of Approximate Reasoning. 53, 4, p. 447–466 20 p.

Research output: Contribution to journalJournal articleResearchpeer-review

File
Collaborative filtering
Collaborative Filtering
Recommender systems
Recommender Systems
Dimensionality Reduction
50 Citations (Scopus)
489 Downloads (Pure)

Mixtures of truncated basis functions

Langseth, H., Nielsen, T. D., Rumí, R. & Salmerón, A., 2012, In : International Journal of Approximate Reasoning. 53, 2, p. 212-227

Research output: Contribution to journalJournal articleResearchpeer-review

File
Basis Functions
Approximation
Polynomials
Polynomial
Fourier series
2011
11 Citations (Scopus)
606 Downloads (Pure)

Probabilistic decision graphs for optimization under uncertainty

Jensen, F. V. & Nielsen, T. D., 2011, In : 4OR. 9, 1, p. 1-28 28 p.

Research output: Contribution to journalJournal articleResearchpeer-review

File
Influence Diagrams
Decision problem
Uncertainty
Optimization
Graph in graph theory
2010
26 Citations (Scopus)
309 Downloads (Pure)

Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials

Langseth, H., Nielsen, T. D., Rumí, R. & Salmerón, A., Jun 2010, In : International Journal of Approximate Reasoning. 51, 5, p. 485-498

Research output: Contribution to journalJournal articleResearchpeer-review

File
Model Selection
Parameter estimation
Parameter Estimation
Likelihood
Regression
2009
9 Citations (Scopus)
408 Downloads (Pure)

A comparison of two approaches for solving unconstrained influence diagrams

Ahlmann-Ohlsen, K. S., Jensen, F. V., Nielsen, T. D., Pedersen, O. & Vomlelová, M., 2009, In : International Journal of Approximate Reasoning. 50, 1, p. 153-173

Research output: Contribution to journalJournal articleResearchpeer-review

File
Influence Diagrams
Decision trees
Specifications
Decision problem
Partial ordering
60 Citations (Scopus)
1054 Downloads (Pure)

Inference in hybrid Bayesian networks

Lanseth, H., Nielsen, T. D., Rumí, R. & Salmerón, A., 2009, In : Reliability Engineering & System Safety. 94, 10, p. 1499–1509

Research output: Contribution to journalJournal articleResearchpeer-review

File
Bayesian networks
Large scale systems
Engines
7 Citations (Scopus)
449 Downloads (Pure)

Latent Classification Models for Binary Data

Langseth, H. & Nielsen, T. D., 2009, In : Pattern Recognition. 42, 11, p. 2724-2736

Research output: Contribution to journalJournal articleResearchpeer-review

File
Classifiers
Bayesian networks
2008
27 Citations (Scopus)
235 Downloads (Pure)

Adapting Bayes Network Structures to Non-stationary Domains

Nielsen, S. H. & Nielsen, T. D., 2008, In : International Journal of Approximate Reasoning. 49, 2, p. 379-397

Research output: Contribution to journalJournal articleResearchpeer-review

File
Bayesian networks
Bayes
Network Structure
Bayesian Networks
Sampling
2007
4 Citations (Scopus)
288 Downloads (Pure)

On-line Alert Systems for Production Plants: A Conflict Based Approach

Nielsen, T. D. & Jensen, F. V., 2007, In : International Journal of Approximate Reasoning. 45, 2, p. 255-270

Research output: Contribution to journalJournal articleResearchpeer-review

File
Online systems
Fault
Fault detection
Fault Detection
Methodology
2006
49 Citations (Scopus)
705 Downloads (Pure)

Classification using Hierarchical Naive Bayes models

Langseth, H. & Dyhre Nielsen, T., 2006, In : Machine Learning. 63, 2, p. 135-159

Research output: Contribution to journalJournal articleResearchpeer-review

File
Classifiers
Learning systems
17 Citations (Scopus)
772 Downloads (Pure)

Dynamic decision making without expected utility: an operational approach

Nielsen, T. D. & Jaffray, J-Y., 2006, In : European Journal of Operational Research. 169, 1, p. 226-246

Research output: Contribution to journalJournal articleResearchpeer-review

File
Expected Utility
Decision trees
Utility Theory
Decision making
Decision Making
18 Citations (Scopus)
229 Downloads (Pure)

Sequential influence diagrams: a unified asymmetry framework

Jensen, F. V., Nielsen, T. D. & Shenoy, P. P., 2006, In : International Journal of Approximate Reasoning. 42, 1-2, p. 101-118

Research output: Contribution to journalJournal articleResearchpeer-review

File
Influence Diagrams
Asymmetry
Framework
2005
13 Citations (Scopus)

Latent classification models

Langseth, H. & Nielsen, T. D., 2005, In : Machine Learning. 59, 3, p. 237-265

Research output: Contribution to journalJournal articleResearchpeer-review

Classifiers
2004
31 Citations (Scopus)

Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains

Langseth, H. & Nielsen, T. D., 2004, In : Journal of Machine Learning Research. 4, 3, p. 339-368

Research output: Contribution to journalJournal articleResearchpeer-review

25 Citations (Scopus)

Latent variable discovery in classification models

Zhang, N. L., Nielsen, T. D. & Jensen, F. V., 2004, In : Artificial Intelligence in Medicine. 30, 3, p. 283-299

Research output: Contribution to journalJournal articleResearchpeer-review

24 Citations (Scopus)

Learning a decision maker's utility function from (possibly) inconsistent behavior

Nielsen, T. D. & Jensen, F. V., 2004, In : Artificial Intelligence. 160, 1-2, p. 53-78 25 p.

Research output: Contribution to journalJournal articleResearchpeer-review

decision maker
learning
decision model
Computer science
learning method
2003

Representing and Solving Asymmetric Decision Problems

Nielsen, T. D. & Jensen, F. V., 2003, In : International Journal of Information Technology and Decision Making. 2, 2, p. 217-263

Research output: Contribution to journalJournal articleResearchpeer-review

20 Citations (Scopus)

Sensitivity analysis for influence diagrams

Nielsen, T. D. & Jensen, F. V., 2003, In : IEEE Transactions of Cybernetics, Man and Machines. 33, 2, p. 223-234

Research output: Contribution to journalJournal articleResearchpeer-review

20 Citations (Scopus)

Sensitivity analysis in influence diagrams

Nielsen, T. D. & Jensen, F. V., 2003, In : IEEE Transactions on Systems Man and Cybernetics - Part A - Systems and Humans. 33, 2, p. 223-234

Research output: Contribution to journalJournal articleResearchpeer-review

2002
3 Citations (Scopus)

Decomposition of influence diagrams

Nielsen, T. D., 2002, In : Journal of Applied Non-Classical Logics. 12, 2, p. 135-150

Research output: Contribution to journalJournal articleResearchpeer-review