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Langseth, Helge Author

Open Access

Learning Mixtures of Truncated Basis Functions from Data

  • Langseth H.
  • Nielsen T.
  • Pérez-Bernabé I.
  • Salmerón A.

International Journal of Approximate Reasoning - 1/1/2014

10.1016/j.ijar.2013.09.012

Cite count: 23 (Web of Science) 9 (Scopus)
  • JCR Quartile: Q1 (2014)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.451 (2022)
  • Category normalized Impact: 0.81 (2014)
  • CiteScore: 7.1 (2020)
  • SJR: 1.46 (2014
  • SNIP: 2.845 (2014
  • JCR 5-year Impact Factor: 2.51
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)

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

  • Zhong, Shengtong
  • Langseth, Helge
  • Nielsen, Thomas Dyhre

RELIABILITY ENGINEERING and SYSTEM SAFETY - 1/01/2014

10.1016/j.ress.2013.07.016

Cite count: 5 (Web of Science) 4 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.41 (2014)
  • CiteScore: 9.3 (2020)
  • SJR: 1.419 (2014
  • SNIP: 2.616 (2014
  • JCR 5-year Impact Factor: 2.693
  • JCR Categories: OPERATIONS RESEARCH & MANAGEMENT SCIENCE
  • SJR Categories: Applied Mathematics (Q1); Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1)
Open Access

A latent model for collaborative filtering

  • Langseth H.
  • Nielsen T.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/6/2012

10.1016/j.ijar.2011.11.002

Cite count: 23 (Web of Science) 31 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.729 (2012)
  • CiteScore: 7.1 (2020)
  • SJR: 1.494 (2012
  • SNIP: 2.132 (2012
  • JCR 5-year Impact Factor: 2.165
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)

Frontiers in Artificial Intelligence and Applications: Preface

  • Kofod-Petersen A.
  • Heintz F.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

Cite count:
  • SJR Quartile: Q3
  • CiteScore: 0.6 (2020)
  • SJR: 0.246 (2011
  • SNIP: 0.583 (2011
  • SJR Categories: Artificial Intelligence (Q3)
Open Access

Parameter Estimation and Model Selection for Mixtures of Truncated Exponentials

  • Antonio Salmerón Cerdán
  • Rafael Rumí Rodríguez
  • Thomas D. Nielsen
  • Helge Langseth

International Journal of Approximate Reasoning - 1/06/2010

10.1016/j.ijar.2010.01.008

Cite count: 22 (Web of Science) 27 (Scopus)
  • JCR Quartile: Q2 (2010)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.684 (2010)
  • Category normalized Impact: 0.66 (2010)
  • CiteScore: 7.1 (2020)
  • SJR: 1.329 (2010
  • SNIP: 1.971 (2010
  • JCR 5-year Impact Factor: 1.72
  • JCR Categories: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • SJR Categories: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
Open Access

Maximum Likelihood Learning of Conditional MTE Distributions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Lecture Notes in Computer Science - 27/8/2009

10.1007/978-3-642-02906-6_22

Cite count: 9 (Web of Science) 14 (Scopus)
  • JCR Quartile: Q2 (2009)
  • Category normalized Impact: 1.409 (2009)
  • CiteScore: 1.8 (2020)
  • SJR: 0.302 (2009
  • SNIP: 0.586 (2009

Latent Classification Models for Binary Data

  • Langseth H.
  • Nielsen T.

Pattern Recognition - 1/11/2009

10.1016/j.patcog.2009.05.002

Cite count: 8 (Web of Science) 8 (Scopus)
  • SJR Quartile: Q1
  • JCR Impact Factor: 2.554 (2009)
  • CiteScore: 15.7 (2020)
  • SJR: 1.163 (2009
  • SNIP: 2.837 (2009
  • JCR 5-year Impact Factor: 3.453
  • JCR Categories: ENGINEERING, ELECTRICAL & ELECTRONIC
  • SJR Categories: Artificial Intelligence (Q1); Computer Vision and Pattern Recognition (Q1); Signal Processing (Q1); Software (Q1)

Inference in hybrid Bayesian networks

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

RELIABILITY ENGINEERING and SYSTEM SAFETY - 1/10/2009

10.1016/j.ress.2009.02.027

Cite count: 71 (Web of Science) 75 (Scopus)
  • JCR Quartile: Q1 (2009)
  • SJR Quartile: Q1
  • JCR Impact Factor: 1.908 (2009)
  • Category normalized Impact: 2.242 (2009)
  • CiteScore: 9.3 (2020)
  • SJR: 1.142 (2009
  • SNIP: 2.571 (2009
  • JCR 5-year Impact Factor: 2.305
  • JCR Categories: ENGINEERING, INDUSTRIAL
  • SJR Categories: Applied Mathematics (Q1); Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1)

Bayesian networks in reliability

  • Langseth H.
  • Portinale L.

Reliability Engineering and System Safety - 1/1/2007

10.1016/j.ress.2005.11.037

Cite count: 436 (Scopus)
  • SJR Quartile: Q1
  • CiteScore: 9.3 (2020)
  • SJR: 0.74 (2007
  • SNIP: 2.203 (2007
  • SJR Categories: Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q1); Applied Mathematics (Q2)

Modelling of dependence between critical failure and preventive maintenance: The repair alert model

  • Lindqvist B.
  • Støve B.
  • Langseth H.

Journal of Statistical Planning and Inference - 1/5/2006

10.1016/j.jspi.2004.10.033

Cite count: 22 (Scopus)
  • SJR Quartile: Q2
  • CiteScore: 1.4 (2020)
  • SJR: 0.937 (2006
  • SNIP: 1.051 (2006
  • SJR Categories: Applied Mathematics (Q2); Statistics and Probability (Q2); Statistics, Probability and Uncertainty (Q2)

Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas

  • Inmaculada Pérez-Bernabé
  • Antonio Salmerón Cerdán
  • Helge Langseth

2015

Cite count:
  • Dialnet

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Proceedings of the Sixth European Workshop on Probabilistic Graphical Models - 1/12/2012

Cite count: 11 (Scopus)
  • SJR Categories: Statistics and Probability

Bayesian networks in reliability: The good, the bad, and the ugly

  • Langseth H.

Advances in Mathematical Modeling for Reliability - 1/5/2008

Cite count: 14 (Scopus)

Applications of Bayesian networks in reliability analysis

  • Langseth H.
  • Portinale L.

Bayesian Network Technologies: Applications and Graphical Models - 1/12/2007

10.4018/978-1-59904-141-4.ch005

Cite count: 7 (Scopus)
Open Access

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2023

Cite count:
  • CiteScore: 1.1 (2022)
  • SJR: 0.202 (2022
  • SNIP: 0.223 (2022

Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders

  • Bjørnar Vassøy
  • Helge Langseth
  • Benjamin Kille

Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023 - 14/09/2023

10.1145/3604915.3608842

Cite count:

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 1st ACM Conference on Reproducibility and Replicability, REP 2023 - 27/06/2023

10.1145/3589806.3600044

Cite count:

Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches

  • Tiwari, Shweta
  • Bell, Gavin
  • Langseth, Helge
  • Ramampiaro, Heri
  • Rocha, AP
  • Steels, L
  • VandenHerik, J
... View more Collapse

ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3 - 2022

10.5220/0010991800003116

Comparative study of event prediction in power grids using supervised machine learning methods

  • Hoiem K.W.
  • Santi V.
  • Torsater B.N.
  • Langseth H.
  • Andresen C.A.
  • Rosenlund G.H.

SEST 2020 - 3rd International Conference on Smart Energy Systems and Technologies - 1/9/2020

10.1109/sest48500.2020.9203025

Cite count: 2 (Scopus)

Prediction intervals: Split normal mixture from quality-driven deep ensembles

  • Salem T.S.
  • Langseth H.
  • Ramampiaro H.

Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence, UAI 2020 - 1/1/2020

Cite count: 1 (Scopus)

Forecasting intra-hour imbalances in electric power systems

  • Salem T.S.
  • Kathuria K.
  • Ramampiaro H.
  • Langseth H.

33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 - 1/1/2019

Cite count: 4 (Scopus)

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

  • Zeng M.
  • Gao H.
  • Yu T.
  • Mengshoel O.
  • Langseth H.
  • Lane I.
  • Liu X.
... View more Collapse

Proceedings - International Symposium on Wearable Computers, ISWC - 8/10/2018

10.1145/3267242.3267286

Cite count: 54 (Scopus)
  • SJR Categories: Computer Networks and Communications; Engineering (miscellaneous); Hardware and Architecture; Software

Inter-session modeling for session-based recommendation

  • Ruocco M.
  • Skrede O.
  • Langseth H.

ACM International Conference Proceeding Series - 27/8/2017

10.1145/3125486.3125491

Cite count: 25 (Scopus)
  • SJR Categories: Ocean Engineering
Open Access

Data driven case base construction for prediction of success of marine operations

  • Mathisen B.
  • Aamodt A.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2017

Cite count: 1 (Scopus)
  • CiteScore: 0.8 (2020)
  • SJR: 0.167 (2017
  • SNIP: 0.346 (2017
  • SJR Categories: Computer Science (miscellaneous)

This author has no patents.

This author has no reports or other types of publications.

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 13

Last data update: 5/18/24 9:32 AM
Next scheduled update: 5/25/24 3:00 AM