Helge Langseth

According to our database1, Helge Langseth authored at least 67 papers between 2001 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches.
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021
Probabilistic Models with Deep Neural Networks.
Entropy, 2021

Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities.
CoRR, 2021

Machine Learning in Financial Market Surveillance: A Survey.
IEEE Access, 2021

2020
Learning similarity measures from data.
Prog. Artif. Intell., 2020

Analyzing concept drift: A case study in the financial sector.
Intell. Data Anal., 2020

Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019
AMIDST: A Java toolbox for scalable probabilistic machine learning.
Knowl. Based Syst., 2019

Securing Tag-based recommender systems against profile injection attacks: A comparative study. (Extended Report).
CoRR, 2019

Forecasting Intra-Hour Imbalances in Electric Power Systems.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

New Ideas in Ranking for Personalized Fashion Recommender Systems.
Proceedings of the Business and Consumer Analytics: New Ideas, 2019

2018
A Review of Inference Algorithms for Hybrid Bayesian Networks.
J. Artif. Intell. Res., 2018

A deep network model for paraphrase detection in short text messages.
Inf. Process. Manag., 2018

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks.
Int. J. Approx. Reason., 2018

Securing Tag-based recommender systems against profile injection attacks: A comparative study.
CoRR, 2018

Detecting Offensive Language in Tweets Using Deep Learning.
CoRR, 2018

Effective hate-speech detection in Twitter data using recurrent neural networks.
Appl. Intell., 2018

Understanding and improving recurrent networks for human activity recognition by continuous attention.
Proceedings of the 2018 ACM International Symposium on Wearable Computers, 2018

2017
MAP inference in dynamic hybrid Bayesian networks.
Prog. Artif. Intell., 2017

A parallel algorithm for Bayesian network structure learning from large data sets.
Knowl. Based Syst., 2017

Scaling up Bayesian variational inference using distributed computing clusters.
Int. J. Approx. Reason., 2017

Inter-Session Modeling for Session-Based Recommendation.
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, 2017

Content-Based Social Recommendation with Poisson Matrix Factorization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Bayesian Models of Data Streams with Hierarchical Power Priors.
Proceedings of the 34th International Conference on Machine Learning, 2017

Data Driven Case Base Construction for Prediction of Success of Marine Operations.
Proceedings of ICCBR 2017 Workshops (CAW, 2017

2016
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

d-VMP: Distributed Variational Message Passing.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Financial Data Analysis with PGMs Using AMIDST.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015
Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning.
IEEE Trans. Smart Grid, 2015

Scalable learning of probabilistic latent models for collaborative filtering.
Decis. Support Syst., 2015

Dynamic Bayesian modeling for risk prediction in credit operations.
Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence, 2015

Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data.
Proceedings of the 2015 International ACM Recommender Systems Challenge, 2015

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

MPE Inference in Conditional Linear Gaussian Networks.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Learning Conditional Distributions Using Mixtures of Truncated Basis Functions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Parallel Importance Sampling in Conditional Linear Gaussian Networks.
Proceedings of the Advances in Artificial Intelligence, 2015

Parallelisation of the PC Algorithm.
Proceedings of the Advances in Artificial Intelligence, 2015

2014
A classification-based approach to monitoring the safety of dynamic systems.
Reliab. Eng. Syst. Saf., 2014

Learning mixtures of truncated basis functions from data.
Int. J. Approx. Reason., 2014

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Requirement Engineering for a Small Project with Pre-Specified Scope.
Proceedings of the 27th Norsk Informatikkonferanse, 2014

Learning to Rank for Personalised Fashion Recommender Systems via Implicit Feedback.
Proceedings of the Mining Intelligence and Knowledge Exploration, 2014

2013
Beating the bookie: A look at statistical models for prediction of football matches.
Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Fast Approximate Inference in Hybrid Bayesian Networks Using Dynamic Discretisation.
Proceedings of the Natural and Artificial Models in Computation and Biology, 2013

Effects of data cleansing on load prediction algorithms.
Proceedings of the IEEE Symposium on Computational Intelligence Applications in Smart Grid, 2013

2012
Mixtures of truncated basis functions.
Int. J. Approx. Reason., 2012

A latent model for collaborative filtering.
Int. J. Approx. Reason., 2012

2011
Extended Abstract: A design for a tourist CF system.
Proceedings of the Eleventh Scandinavian Conference on Artificial Intelligence, 2011

Extended Abstract: Combining CBR and BN using metareasoning.
Proceedings of the Eleventh Scandinavian Conference on Artificial Intelligence, 2011

A hybrid CBR and BN architecture refined through data analysis.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

2010
Parameter estimation and model selection for mixtures of truncated exponentials.
Int. J. Approx. Reason., 2010

Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support.
Proceedings of the Intelligent Information Processing V, 2010

Towards a More Expressive Model for Dynamic Classification.
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009
Inference in hybrid Bayesian networks.
Reliab. Eng. Syst. Saf., 2009

Latent classification models for binary data.
Pattern Recognit., 2009

Maximum Likelihood Learning of Conditional MTE Distributions.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

2007
Bayesian networks in reliability.
Reliab. Eng. Syst. Saf., 2007

2006
Classification using Hierarchical Naïve Bayes models.
Mach. Learn., 2006

2005
Latent Classification Models.
Mach. Learn., 2005

2003
Decision theoretic troubleshooting of coherent systems.
Reliab. Eng. Syst. Saf., 2003

Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains.
J. Mach. Learn. Res., 2003

2002
Bayesian networks with applications in reliability analysis.
PhD thesis, 2002

2001
Parameter Learning in Object-Oriented Bayesian Networks.
Ann. Math. Artif. Intell., 2001

The SACSO methodology for troubleshooting complex systems.
Artif. Intell. Eng. Des. Anal. Manuf., 2001

Heuristics for Two Extensions of Basic Troubleshooting.
Proceedings of the SCAI'01, 2001

Structural Learning in Object Oriented Domains.
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, 2001


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