Helge Langseth

According to our database, Helge Langseth authored at least 79 papers between 2001 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Probing the Robustness of Time-series Forecasting Models with CounterfacTS.

Håkon Hanisch Kjærnli, Lluis Mas-Ribas, Aida Ashrafi, Gleb Sizov, Helge Langseth, Odd Erik Gundersen

CoRR, 2024

Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation.

Bjørnar Vassøy, Helge Langseth

Artif. Intell. Rev., 2024

2023

The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning.

Ludvig Killingberg, Helge Langseth

Trans. Mach. Learn. Res., 2023

Lecture Notes in Probabilistic Diffusion Models.

Inga Strümke, Helge Langseth

CoRR, 2023

Deep Contextual Grid Triplet Network for Context-Aware Recommendation.

Sofia Aftab, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco

IEEE Access, 2023

Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders.

Bjørnar Vassøy, Helge Langseth, Benjamin Kille

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Bayesian Exploration in Deep Reinforcement Learning.

Ludvig Killingberg, Helge Langseth

Proceedings of the 5th Symposium of the Norwegian AI Society, 2023

mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites.

David Baumgartner, Helge Langseth, Heri Ramampiaro, Kenth Engø-Monsen

Proceedings of the IEEE International Conference on Big Data, 2023

On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness.

Odd Erik Gundersen, Saeid Shamsaliei, Håkon Sletten Kjærnli, Helge Langseth

Proceedings of the 2023 ACM Conference on Reproducibility and Replicability, 2023

ASAP: Attention-Based State Space Abstraction for Policy Summarization.

Yanzhe Bekkemoen, Helge Langseth

Proceedings of the Asian Conference on Machine Learning, 2023

2022

A data-driven modular architecture with denoising autoencoders for health indicator construction in a manufacturing process.

Emil Blixt Hansen, Helge Langseth, Nadeem Iftikhar, Simon Bøgh

CoRR, 2022

A Reparameterization of Mixtures of Truncated Basis Functions and its Applications.

Antonio Salmerón, Helge Langseth, Andrés R. Masegosa, Thomas D. Nielsen

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches.

Shweta Tiwari, Gavin Bell, Helge Langseth, Heri Ramampiaro

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021

Probabilistic Models with Deep Neural Networks.

Andrés R. Masegosa, Rafael Cabañas, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón

Entropy, 2021

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

Yanzhe Bekkemoen, Helge Langseth

CoRR, 2021

Machine Learning in Financial Market Surveillance: A Survey.

Shweta Tiwari, Heri Ramampiaro, Helge Langseth

IEEE Access, 2021

2020

Learning similarity measures from data.

Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach, Helge Langseth

Prog. Artif. Intell., 2020

Analyzing concept drift: A case study in the financial sector.

Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón

Intell. Data Anal., 2020

Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles.

Tárik S. Salem, Helge Langseth, Heri Ramampiaro

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

AMIDST: A Java toolbox for scalable probabilistic machine learning.

Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

Knowl. Based Syst., 2019

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

Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth

CoRR, 2019

Forecasting Intra-Hour Imbalances in Electric Power Systems.

Tárik S. Salem, Karan Kathuria, Heri Ramampiaro, Helge Langseth

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

New Ideas in Ranking for Personalized Fashion Recommender Systems.

Heri Ramampiaro, Helge Langseth, Thomas Almenningen, Herman Schistad, Martin Havig, Hai Thanh Nguyen

Proceedings of the Business and Consumer Analytics: New Ideas, 2019

2018

A Review of Inference Algorithms for Hybrid Bayesian Networks.

Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

J. Artif. Intell. Res., 2018

A deep network model for paraphrase detection in short text messages.

Basant Agarwal, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco

Inf. Process. Manag., 2018

Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks.

Darío Ramos-López, Andrés R. Masegosa, Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen

Int. J. Approx. Reason., 2018

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

Georgios Pitsilis, Heri Ramampiaro, Helge Langseth

CoRR, 2018

Detecting Offensive Language in Tweets Using Deep Learning.

Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth

CoRR, 2018

Effective hate-speech detection in Twitter data using recurrent neural networks.

Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth

Appl. Intell., 2018

Understanding and improving recurrent networks for human activity recognition by continuous attention.

Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu

Proceedings of the 2018 ACM International Symposium on Wearable Computers, 2018

2017

MAP inference in dynamic hybrid Bayesian networks.

Darío Ramos-López, Andrés R. Masegosa, Ana M. Martínez, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Prog. Artif. Intell., 2017

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

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen

Knowl. Based Syst., 2017

Scaling up Bayesian variational inference using distributed computing clusters.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Int. J. Approx. Reason., 2017

Inter-Session Modeling for Session-Based Recommendation.

Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth

Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, 2017

Content-Based Social Recommendation with Poisson Matrix Factorization.

Eliezer de Souza da Silva, Helge Langseth, Heri Ramampiaro

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Bayesian Models of Data Streams with Hierarchical Power Priors.

Andrés R. Masegosa, Thomas D. Nielsen, Helge Langseth, Darío Ramos-López, Antonio Salmerón, Anders L. Madsen

Proceedings of the 34th International Conference on Machine Learning, 2017

Data Driven Case Base Construction for Prediction of Success of Marine Operations.

Bjørn Magnus Mathisen, Agnar Aamodt, Helge Langseth

Proceedings of ICCBR 2017 Workshops (CAW, 2017

2016

Scalable MAP inference in Bayesian networks based on a Map-Reduce approach.

Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

d-VMP: Distributed Variational Message Passing.

Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

Financial Data Analysis with PGMs Using AMIDST.

Rafael Cabañas, Ana M. Martínez, Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs.

Antonio Salmerón, Anders L. Madsen, Frank Jensen, Helge Langseth, Thomas D. Nielsen, Darío Ramos-López, Ana M. Martínez, Andrés R. Masegosa

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.

Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth, Pinar Öztürk

IEEE Trans. Smart Grid, 2015

Scalable learning of probabilistic latent models for collaborative filtering.

Helge Langseth, Thomas D. Nielsen

Decis. Support Syst., 2015

Dynamic Bayesian modeling for risk prediction in credit operations.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence, 2015

Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data.

Øyvind H. Myklatun, Thorstein K. Thorrud, Hai Thanh Nguyen, Helge Langseth, Anders Kofod-Petersen

Proceedings of the 2015 International ACM Recommender Systems Challenge, 2015

Modeling Concept Drift: A Probabilistic Graphical Model Based Approach.

Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Antonio Fernández, Anders L. Madsen, Ramón Sáez

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

MPE Inference in Conditional Linear Gaussian Networks.

Antonio Salmerón, Rafael Rumí, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Learning Conditional Distributions Using Mixtures of Truncated Basis Functions.

Inmaculada Pérez-Bernabé, Antonio Salmerón, Helge Langseth

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

Parallel Importance Sampling in Conditional Linear Gaussian Networks.

Antonio Salmerón, Darío Ramos-López, Hanen Borchani, Ana M. Martínez, Andrés R. Masegosa, Antonio Fernández, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen

Proceedings of the Advances in Artificial Intelligence, 2015

Parallelisation of the PC Algorithm.

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen

Proceedings of the Advances in Artificial Intelligence, 2015

2014

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

Shengtong Zhong, Helge Langseth, Thomas Dyhre Nielsen

Reliab. Eng. Syst. Saf., 2014

Learning mixtures of truncated basis functions from data.

Helge Langseth, Thomas D. Nielsen, Inmaculada Pérez-Bernabé, Antonio Salmerón

Int. J. Approx. Reason., 2014

A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs.

Anders L. Madsen, Frank Jensen, Antonio Salmerón, Martin Karlsen, Helge Langseth, Thomas D. Nielsen

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Requirement Engineering for a Small Project with Pre-Specified Scope.

Thomas D. Nielsen, Sigve Hovda, Antonio Fernández, Helge Langseth, Anders L. Madsen, Andrés R. Masegosa, Antonio Salmerón

Proceedings of the 27th Norsk Informatikkonferanse, 2014

Learning to Rank for Personalised Fashion Recommender Systems via Implicit Feedback.

Hai Thanh Nguyen, Thomas Almenningen, Martin Havig, Herman Schistad, Anders Kofod-Petersen, Helge Langseth, Heri Ramampiaro

Proceedings of the Mining Intelligence and Knowledge Exploration, 2014

2013

Beating the bookie: A look at statistical models for prediction of football matches.

Helge Langseth

Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, 2013

Fast Approximate Inference in Hybrid Bayesian Networks Using Dynamic Discretisation.

Helge Langseth, David Marquez, Martin Neil

Proceedings of the Natural and Artificial Models in Computation and Biology, 2013

Effects of data cleansing on load prediction algorithms.

Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth

Proceedings of the IEEE Symposium on Computational Intelligence Applications in Smart Grid, 2013

2012

Mixtures of truncated basis functions.

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón

Int. J. Approx. Reason., 2012

A latent model for collaborative filtering.

Helge Langseth, Thomas Dyhre Nielsen

Int. J. Approx. Reason., 2012

2011

Extended Abstract: A design for a tourist CF system.

Terje N. Lillegraven, Arnt C. Wolden, Anders Kofod-Petersen, Helge Langseth

Proceedings of the Eleventh Scandinavian Conference on Artificial Intelligence, 2011

Extended Abstract: Combining CBR and BN using metareasoning.

Tor Gunnar Houeland, Tore Bruland, Agnar Aamodt, Helge Langseth

Proceedings of the Eleventh Scandinavian Conference on Artificial Intelligence, 2011

A hybrid CBR and BN architecture refined through data analysis.

Tore Bruland, Agnar Aamodt, Helge Langseth

Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

2010

Parameter estimation and model selection for mixtures of truncated exponentials.

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón

Int. J. Approx. Reason., 2010

Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support.

Tore Bruland, Agnar Aamodt, Helge Langseth

Proceedings of the Intelligent Information Processing V, 2010

Towards a More Expressive Model for Dynamic Classification.

Shengtong Zhong, Ana M. Martínez, Thomas D. Nielsen, Helge Langseth

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

2009

Inference in hybrid Bayesian networks.

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón

Reliab. Eng. Syst. Saf., 2009

Latent classification models for binary data.

Helge Langseth, Thomas D. Nielsen

Pattern Recognit., 2009

Maximum Likelihood Learning of Conditional MTE Distributions.

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

2007

Bayesian networks in reliability.

Helge Langseth, Luigi Portinale

Reliab. Eng. Syst. Saf., 2007

2006

Classification using Hierarchical Naïve Bayes models.

Helge Langseth, Thomas D. Nielsen

Mach. Learn., 2006

2005

Latent Classification Models.

Helge Langseth, Thomas D. Nielsen

Mach. Learn., 2005

2003

Decision theoretic troubleshooting of coherent systems.

Helge Langseth, Finn Verner Jensen

Reliab. Eng. Syst. Saf., 2003

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

Helge Langseth, Thomas D. Nielsen

J. Mach. Learn. Res., 2003

2002

Bayesian networks with applications in reliability analysis.

Helge Langseth

PhD thesis, 2002

2001

Parameter Learning in Object-Oriented Bayesian Networks.

Helge Langseth, Olav Bangsø

Ann. Math. Artif. Intell., 2001

The SACSO methodology for troubleshooting complex systems.

Finn Verner Jensen, Uffe Kjærulff, Brian Kristiansen, Helge Langseth, Claus Skaanning, Jirí Vomlel, Marta Vomlelová

Artif. Intell. Eng. Des. Anal. Manuf., 2001

Heuristics for Two Extensions of Basic Troubleshooting.

Helge Langseth, Finn Verner Jensen

Proceedings of the SCAI'01, 2001

Structural Learning in Object Oriented Domains.

Olav Bangsø, Helge Langseth, Thomas D. Nielsen

Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference, 2001