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Langseth, Helge Autor

Open Access

MAP inference in dynamic hybrid Bayesian networks

  • Ramos-López D.
  • Masegosa A.
  • Martínez A.
  • Salmerón A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
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PROGRESS IN ARTIFICIAL INTELLIGENCE - 27/6/2017

10.1007/s13748-017-0115-7

Número de citas: 6 (Web of Science) 6 (Scopus)
  • Impacto Normalizado por Categoría: 0,228 (2017)
  • CiteScore: 6,3 (2024)
  • SNIP: 0,977 (2017)
  • Categorías SJR: Artificial Intelligence

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

  • Madsen A.
  • Jensen F.
  • Salmerón A.
  • Langseth H.
  • Nielsen T.

KNOWLEDGE-BASED SYSTEMS - 1/2/2017

10.1016/j.knosys.2016.07.031

Número de citas: 72 (Web of Science) 82 (Scopus)
  • Cuartil JCR: Q1 (2017)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 4,396 (2023)
  • Impacto Normalizado por Categoría: 2,128 (2017)
  • CiteScore: 15 (2024)
  • SJR: 1,378 (2017)
  • SNIP: 2,358 (2017)
  • Impacto JCR a 5 años: 4,514
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Artificial Intelligence (Q1); Information Systems and Management (Q1); Management Information Systems (Q1); Software (Q1)

Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning

  • Hoverstad B.
  • Tidemann A.
  • Langseth H.
  • Ozturk P.

IEEE Transactions on Smart Grid - 1/7/2015

10.1109/tsg.2015.2395822

Número de citas: 74 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 3,19 (2015)
  • CiteScore: 21,1 (2024)
  • SJR: 3,424 (2015)
  • SNIP: 3,281 (2015)
  • Impacto JCR a 5 años: 5,104
  • Categorías JCR: ENGINEERING, ELECTRICAL & ELECTRONIC
  • Categorías SJR: Computer Science (miscellaneous) (Q1)

Scalable learning of probabilistic latent models for collaborative filtering

  • Langseth H.
  • Nielsen T.

Decision Support Systems - 1/6/2015

10.1016/j.dss.2015.03.006

Número de citas: 16 (Web of Science) 22 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,604 (2015)
  • CiteScore: 13,5 (2024)
  • SJR: 1,87 (2015)
  • SNIP: 2,284 (2015)
  • Impacto JCR a 5 años: 3,271
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Arts and Humanities (miscellaneous) (Q1); Developmental and Educational Psychology (Q1); Information Systems (Q1); Information Systems and Management (Q1); Management Information Systems (Q1)
Open Access

Learning mixtures of truncated basis functions from data

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

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/6/2014

10.1016/j.ijar.2013.09.012

Número de citas: 26 (Web of Science) 9 (Scopus)
  • Cuartil JCR: Q1 (2014)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,451 (2022)
  • Impacto Normalizado por Categoría: 0,81 (2014)
  • CiteScore: 6,2 (2024)
  • SJR: 1,494 (2012)
  • SNIP: 2,122 (2012)
  • Impacto JCR a 5 años: 2,51
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: 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

Número de citas: 5 (Web of Science) 6 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 2,41 (2014)
  • CiteScore: 19,1 (2024)
  • SJR: 1,419 (2014)
  • SNIP: 2,592 (2014)
  • Impacto JCR a 5 años: 2,693
  • Categorías JCR: OPERATIONS RESEARCH & MANAGEMENT SCIENCE
  • Categorías SJR: 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

Número de citas: 23 (Web of Science) 38 (Scopus)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 1,729 (2012)
  • CiteScore: 6,2 (2024)
  • SJR: 1,494 (2012)
  • SNIP: 2,122 (2012)
  • Impacto JCR a 5 años: 2,165
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
Open Access

Mixtures of truncated basis functions

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

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/2/2012

10.1016/j.ijar.2011.10.004

Número de citas: 63 (Web of Science) 71 (Scopus)
  • Cuartil JCR: Q2 (2012)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 1,729 (2012)
  • Impacto Normalizado por Categoría: 1,763 (2012)
  • CiteScore: 6,2 (2024)
  • SJR: 1,494 (2012)
  • SNIP: 2,122 (2012)
  • Impacto JCR a 5 años: 2,165
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: 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

Número de citas: 0 (Scopus)
  • Cuartil SJR: Q3
  • CiteScore: 0,7 (2024)
  • SJR: 0,246 (2011)
  • SNIP: 0,586 (2011)
  • Categorías SJR: 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 - 1/6/2010

10.1016/j.ijar.2010.01.008

Número de citas: 23 (Web of Science) 29 (Scopus) 0 (Dialnet)
  • Cuartil JCR: Q2 (2010)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 1,684 (2010)
  • Impacto Normalizado por Categoría: 0,66 (2010)
  • CiteScore: 6,2 (2024)
  • SJR: 1,329 (2010)
  • SNIP: 1,995 (2010)
  • Impacto JCR a 5 años: 1,72
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)

New Ideas in Ranking for Personalized Fashion Recommender Systems Libro

  • Ramampiaro H.
  • Langseth H.
  • Almenningen T.
  • Schistad H.
  • Havig M.
  • Nguyen H.T.

Business and Consumer Analytics New Ideas - 1/1/2019

10.1007/978-3-030-06222-4_25

Número de citas: 2 (Scopus)

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

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

2015

Número de citas: 0 (Dialnet)
  • Dialnet

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

  • Langseth H.

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

Número de citas: 14 (Scopus)

Applications of Bayesian networks in reliability analysis Libro

  • Langseth H.
  • Portinale L.

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

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

Número de citas: 8 (Scopus)

STATISTICAL MODELING AND INFERENCE FOR COMPONENT FAILURE TIMES UNDER PREVENTIVE MAINTENANCE AND INDEPENDENT CENSORING Libro

  • Lindqvist B.H.
  • Langseth H.

Series on Quality Reliability and Engineering Statistics Vol 10 Modern Statistical and Mathematical Methods in Reliability - 1/1/2005

10.1142/9789812703378_0023

Número de citas: 3 (Scopus)
Open Access

Opt-in Transparent Fairness for Recommender Systems

  • Bjørnar Vassøy
  • Benjamin Kille
  • Helge Langseth

Lecture Notes in Computer Science - 1/1/2025

10.1007/978-3-031-88708-6_23

Número de citas: 0 (Scopus)
  • CiteScore: 2,4 (2024)
  • SJR: 0,352 (2024)
  • SNIP: 0,555 (2024)
Open Access

A Divide and Conquer Approach for Solving Structural Causal Models

  • Bjøru, Anna Rodum
  • Cabañas De Paz, Rafael
  • Langseth, Helge
  • Salmerón Cerdán, Antonio

INTERNATIONAL CONFERENCE ON PROBABILISTIC GRAPHICAL MODELS - 1/1/2024

Número de citas: 2 (Web of Science) 2 (Scopus)
  • CiteScore: 8,9 (2024)
  • SJR: 1,17 (2024)
  • SNIP: 1,948 (2024)

mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites

  • Baumgartner D.
  • Langseth H.
  • Ramampiaro H.
  • Engo-Monsen K.

Proceedings 2023 IEEE International Conference on Big Data Bigdata 2023 - 1/1/2023

10.1109/bigdata59044.2023.10386980

Número de citas: 1 (Scopus)

ASAP: Attention-Based State Space Abstraction for Policy Summarization

  • Bekkemoen Y.
  • Langseth H.

Proceedings of Machine Learning Research - 1/1/2023

Número de citas: 1 (Scopus)
Open Access

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

Ceur Workshop Proceedings - 1/1/2023

Número de citas: 0 (Scopus)
  • CiteScore: 0,9 (2024)
  • SJR: 0,191 (2023)
  • SNIP: 0,246 (2023)
Open Access

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

Número de citas: 4 (Web of Science) 4 (Scopus)
Open Access

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'23 - 27/06/2023

10.1145/3589806.3600044

Número de citas: 5 (Web of Science) 5 (Scopus)
Open Access

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
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ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3 - 1/1/2022

10.5220/0010991800003116

Número de citas: 0 (Web of Science) 1 (Scopus)
  • CiteScore: 0,9 (2024)
  • SNIP: 1,138 (2022)

A Reparameterization of Mixtures of Truncated Basis Functions and its Applications

  • Antonio Salmerón
  • Helge Langseth
  • Andres Masegosa
  • Thomas Dyhre Nielsen

Proceedings of Machine Learning Research - 1/1/2022

Número de citas: 0 (Scopus)

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

Número de citas: 6 (Scopus)

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Scopus: 22

Web of Science: 12

Scopus: 45

Web of Science: 20

Última actualización de los datos: 30/08/25 12:20
Próxima recolección programada: 6/09/25 3:00