Helge Langseth

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 51

Top Venues

CoRR

Int. J. Approx. Reason.

Probabilistic Graphical Models

CAEPIA

Norwegian University of Science and Technology, Trondheim, Norway (PHD)

Education History

Norwegian University of Science and Technology, Trondheim, Norway

PHD

Publications

Håkon Hanisch Kjærnli, Lluis Mas-Ribas, Aida Ashrafi, Gleb Sizov, Helge Langseth, Odd Erik Gundersen
Probing the Robustness of Time-series Forecasting Models with CounterfacTS. CoRR (2024)
Bjørnar Vassøy, Helge Langseth
Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation. Artif. Intell. Rev. 57 (4) (2024)
David Baumgartner, Helge Langseth, Heri Ramampiaro, Kenth Engø-Monsen
mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites. BigData (2023)
Bjørnar Vassøy, Helge Langseth, Benjamin Kille
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. CoRR (2023)
Ludvig Killingberg, Helge Langseth
Bayesian Exploration in Deep Reinforcement Learning. NAIS (2023)
Inga Strümke, Helge Langseth
Lecture Notes in Probabilistic Diffusion Models. CoRR (2023)
Odd Erik Gundersen, Saeid Shamsaliei, Håkon Sletten Kjærnli, Helge Langseth
On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness. ACM-REP (2023)
Sofia Aftab, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco
Deep Contextual Grid Triplet Network for Context-Aware Recommendation. IEEE Access 11 (2023)
Bjørnar Vassøy, Helge Langseth, Benjamin Kille
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. RecSys (2023)
Ludvig Killingberg, Helge Langseth
The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Bjørnar Vassøy, Helge Langseth
Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation. CoRR (2023)
Yanzhe Bekkemoen, Helge Langseth
ASAP: Attention-Based State Space Abstraction for Policy Summarization. ACML (2023)
Shweta Tiwari, Gavin Bell, Helge Langseth, Heri Ramampiaro
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. ICAART (3) (2022)
Antonio Salmerón, Helge Langseth, Andrés R. Masegosa, Thomas D. Nielsen
A Reparameterization of Mixtures of Truncated Basis Functions and its Applications. PGM (2022)
Emil Blixt Hansen, Helge Langseth, Nadeem Iftikhar, Simon Bøgh
A data-driven modular architecture with denoising autoencoders for health indicator construction in a manufacturing process. CoRR (2022)
Yanzhe Bekkemoen, Helge Langseth
Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities. CoRR (2021)
Shweta Tiwari, Heri Ramampiaro, Helge Langseth
Machine Learning in Financial Market Surveillance: A Survey. IEEE Access 9 (2021)
Andrés R. Masegosa, Rafael Cabañas, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón
Probabilistic Models with Deep Neural Networks. Entropy 23 (1) (2021)
Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach, Helge Langseth
Learning similarity measures from data. CoRR (2020)
Tárik S. Salem, Helge Langseth, Heri Ramampiaro
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. UAI (2020)
Tárik S. Salem, Helge Langseth, Heri Ramampiaro
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. CoRR (2020)
Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach, Helge Langseth
Learning similarity measures from data. Prog. Artif. Intell. 9 (2) (2020)
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón
Analyzing concept drift: A case study in the financial sector. Intell. Data Anal. 24 (3) (2020)
Tárik S. Salem, Karan Kathuria, Heri Ramampiaro, Helge Langseth
Forecasting Intra-Hour Imbalances in Electric Power Systems. AAAI (2019)
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen
AMIDST: A Java toolbox for scalable probabilistic machine learning. Knowl. Based Syst. 163 (2019)
Tárik S. Salem, Karan Kathuria, Heri Ramampiaro, Helge Langseth
Forecasting Intra-Hour Imbalances in Electric Power Systems. CoRR (2019)
Andrés R. Masegosa, Rafael Cabañas, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón
Probabilistic Models with Deep Neural Networks. CoRR (2019)
Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth
Securing Tag-based recommender systems against profile injection attacks: A comparative study. (Extended Report). CoRR (2019)
Basant Agarwal, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco
A deep network model for paraphrase detection in short text messages. Inf. Process. Manag. 54 (6) (2018)
Georgios Pitsilis, Heri Ramampiaro, Helge Langseth
Securing Tag-based recommender systems against profile injection attacks: A comparative study. CoRR (2018)
Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu
Understanding and improving recurrent networks for human activity recognition by continuous attention. UbiComp (2018)
Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth
Detecting Offensive Language in Tweets Using Deep Learning. CoRR (2018)
Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen
A Review of Inference Algorithms for Hybrid Bayesian Networks. J. Artif. Intell. Res. 62 (2018)
Darío Ramos-López, Andrés R. Masegosa, Antonio Salmerón, Rafael Rumí, Helge Langseth, Thomas D. Nielsen, Anders L. Madsen
Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks. Int. J. Approx. Reason. 100 (2018)
Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth
Effective hate-speech detection in Twitter data using recurrent neural networks. Appl. Intell. 48 (12) (2018)
Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention. CoRR (2018)
Andrés R. Masegosa, Thomas D. Nielsen, Helge Langseth, Darío Ramos-López, Antonio Salmerón, Anders L. Madsen
Bayesian Models of Data Streams with Hierarchical Power Priors. ICML (2017)
Eliezer de Souza da Silva, Helge Langseth, Heri Ramampiaro
Content-Based Social Recommendation with Poisson Matrix Factorization. ECML/PKDD (1) (2017)
Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth
Inter-Session Modeling for Session-Based Recommendation. DLRS@RecSys (2017)
Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen
A parallel algorithm for Bayesian network structure learning from large data sets. Knowl. Based Syst. 117 (2017)
Darío Ramos-López, Andrés R. Masegosa, Ana M. Martínez, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
MAP inference in dynamic hybrid Bayesian networks. Prog. Artif. Intell. 6 (2) (2017)
Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen
Scaling up Bayesian variational inference using distributed computing clusters. Int. J. Approx. Reason. 88 (2017)
Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth
Inter-Session Modeling for Session-Based Recommendation. CoRR (2017)
Bjørn Magnus Mathisen, Agnar Aamodt, Helge Langseth
Data Driven Case Base Construction for Prediction of Success of Marine Operations. ICCBR (Workshops) (2017)
Andrés R. Masegosa, Thomas D. Nielsen, Helge Langseth, Darío Ramos-López, Antonio Salmerón, Anders L. Madsen
Bayesian Models of Data Streams with Hierarchical Power Priors. CoRR (2017)
Basant Agarwal, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco
A Deep Network Model for Paraphrase Detection in Short Text Messages. CoRR (2017)
Andrés R. Masegosa, Ana M. Martínez, Darío Ramos-López, Rafael Cabañas, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning. CoRR (2017)
Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. Probabilistic Graphical Models (2016)
Antonio Salmerón, Anders L. Madsen, Frank Jensen, Helge Langseth, Thomas D. Nielsen, Darío Ramos-López, Ana M. Martínez, Andrés R. Masegosa
Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs. ECAI (2016)
Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen
d-VMP: Distributed Variational Message Passing. Probabilistic Graphical Models (2016)
Rafael Cabañas, Ana M. Martínez, Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Thomas D. Nielsen, Helge Langseth, Anders L. Madsen
Financial Data Analysis with PGMs Using AMIDST. ICDM Workshops (2016)
Inmaculada Pérez-Bernabé, Antonio Salmerón, Helge Langseth
Learning Conditional Distributions Using Mixtures of Truncated Basis Functions. ECSQARU (2015)
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)
Helge Langseth, Thomas D. Nielsen
Scalable learning of probabilistic latent models for collaborative filtering. Decis. Support Syst. 74 (2015)
Anders L. Madsen, Frank Jensen, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen
Parallelisation of the PC Algorithm. CAEPIA (2015)
Øyvind H. Myklatun, Thorstein K. Thorrud, Hai Thanh Nguyen, Helge Langseth, Anders Kofod-Petersen
Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data. RecSys Challenge (2015)
Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth, Pinar Öztürk
Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning. IEEE Trans. Smart Grid 6 (4) (2015)
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)
Antonio Salmerón, Rafael Rumí, Helge Langseth, Anders L. Madsen, Thomas D. Nielsen
MPE Inference in Conditional Linear Gaussian Networks. ECSQARU (2015)
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)
Hai Thanh Nguyen, Thomas Almenningen, Martin Havig, Herman Schistad, Anders Kofod-Petersen, Helge Langseth, Heri Ramampiaro
Learning to Rank for Personalised Fashion Recommender Systems via Implicit Feedback. MIKE (2014)
Thomas D. Nielsen, Sigve Hovda, Antonio Fernández, Helge Langseth, Anders L. Madsen, Andrés R. Masegosa, Antonio Salmerón
Requirement Engineering for a Small Project with Pre-Specified Scope. NIK (2014)
Anders L. Madsen, Frank Jensen, Antonio Salmerón, Martin Karlsen, Helge Langseth, Thomas D. Nielsen
A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs. Probabilistic Graphical Models (2014)
Helge Langseth, Thomas D. Nielsen, Inmaculada Pérez-Bernabé, Antonio Salmerón
Learning mixtures of truncated basis functions from data. Int. J. Approx. Reason. 55 (4) (2014)
Shengtong Zhong, Helge Langseth, Thomas Dyhre Nielsen
A classification-based approach to monitoring the safety of dynamic systems. Reliab. Eng. Syst. Saf. 121 (2014)
Helge Langseth
Beating the bookie: A look at statistical models for prediction of football matches. SCAI (2013)
Helge Langseth, David Marquez, Martin Neil
Fast Approximate Inference in Hybrid Bayesian Networks Using Dynamic Discretisation. IWINAC (1) (2013)
Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth
Effects of data cleansing on load prediction algorithms. CIASG (2013)
Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón
Mixtures of truncated basis functions. Int. J. Approx. Reason. 53 (2) (2012)
Helge Langseth, Thomas Dyhre Nielsen
A latent model for collaborative filtering. Int. J. Approx. Reason. 53 (4) (2012)
Terje N. Lillegraven, Arnt C. Wolden, Anders Kofod-Petersen, Helge Langseth
Extended Abstract: A design for a tourist CF system. SCAI (2011)
Tor Gunnar Houeland, Tore Bruland, Agnar Aamodt, Helge Langseth
Extended Abstract: Combining CBR and BN using metareasoning. SCAI (2011)
Tore Bruland, Agnar Aamodt, Helge Langseth
A hybrid CBR and BN architecture refined through data analysis. ISDA (2011)
Tore Bruland, Agnar Aamodt, Helge Langseth
Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. Intelligent Information Processing (2010)
Shengtong Zhong, Ana M. Martínez, Thomas D. Nielsen, Helge Langseth
Towards a More Expressive Model for Dynamic Classification. FLAIRS Conference (2010)
Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón
Parameter estimation and model selection for mixtures of truncated exponentials. Int. J. Approx. Reason. 51 (5) (2010)
Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón
Maximum Likelihood Learning of Conditional MTE Distributions. ECSQARU (2009)
Helge Langseth, Thomas D. Nielsen
Latent classification models for binary data. Pattern Recognit. 42 (11) (2009)
Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón
Inference in hybrid Bayesian networks. Reliab. Eng. Syst. Saf. 94 (10) (2009)
Helge Langseth, Luigi Portinale
Bayesian networks in reliability. Reliab. Eng. Syst. Saf. 92 (1) (2007)
Helge Langseth, Thomas D. Nielsen
Classification using Hierarchical Naïve Bayes models. Mach. Learn. 63 (2) (2006)
Helge Langseth, Thomas D. Nielsen
Latent Classification Models. Mach. Learn. 59 (3) (2005)
Helge Langseth, Thomas D. Nielsen
Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains. J. Mach. Learn. Res. 4 (2003)
Helge Langseth, Finn Verner Jensen
Decision theoretic troubleshooting of coherent systems. Reliab. Eng. Syst. Saf. 80 (1) (2003)
Olav Bangsø, Helge Langseth, Thomas D. Nielsen
Structural Learning in Object Oriented Domains. FLAIRS Conference (2001)
Helge Langseth, Olav Bangsø
Parameter Learning in Object-Oriented Bayesian Networks. Ann. Math. Artif. Intell. 32 (1-4) (2001)
Finn Verner Jensen, Uffe Kjærulff, Brian Kristiansen, Helge Langseth, Claus Skaanning, Jirí Vomlel, Marta Vomlelová
The SACSO methodology for troubleshooting complex systems. Artif. Intell. Eng. Des. Anal. Manuf. 15 (4) (2001)
Helge Langseth, Finn Verner Jensen
Heuristics for Two Extensions of Basic Troubleshooting. SCAI (2001)

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Publication Activity (10 Years)

Top Topics

Top Venues

Helge Langseth