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Langseth, Helge Autor

Analysis of OREDA data for maintenance optimisation

  • Langseth H.
  • Haugen K.
  • Sandtorv H.

Reliability Engineering and System Safety - 1/1/1998

10.1016/s0951-8320(98)83003-2

Número de citas: 18 (Scopus)
  • CiteScore: 9,3 (2020)

Uncertainty bounds for a monotone multistate system

  • Langseth H.
  • Lindqvist B.

Probability in the Engineering and Informational Sciences - 1/12/1998

10.1017/s0269964800005179

Número de citas: 10 (Scopus)
  • CiteScore: 1,7 (2020)

Parameter learning in object-oriented Bayesian networks

  • Langseth H.
  • Bangsø O.

Annals of Mathematics and Artificial Intelligence - 1/12/2001

10.1023/a:1016769618900

Número de citas: 27 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 2,5 (2020)
  • SJR: 0,747 (2001)
  • SNIP: 1,542 (2001)
  • Categorías SJR: Applied Mathematics (Q2); Artificial Intelligence (Q2)

The SACSO methodology for troubleshooting complex systems

  • Jensen F.
  • Kjærulff U.
  • Kristiansen B.
  • Langseth H.
  • Skaanning C.
  • Vomlel J.
  • Vomlelová M.
... Ver más Contraer

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM - 1/9/2001

10.1017/s0890060401154065

Número de citas: 55 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 2,9 (2020)
  • SJR: 0,365 (2001)
  • SNIP: 0,885 (2001)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Artificial Intelligence (Q3)

Decision theoretic troubleshooting of coherent systems

  • Langseth H.
  • Jensen F.

Reliability Engineering and System Safety - 1/4/2003

10.1016/s0951-8320(02)00202-8

Número de citas: 25 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 9,3 (2020)
  • SJR: 0,414 (2003)
  • SNIP: 1,307 (2003)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q2); Applied Mathematics (Q3)
Open Access

Fusion of domain knowledge with data for structural learning in object oriented domains

  • Langseth H.
  • Nielsen T.

Journal of Machine Learning Research - 1/4/2004

10.1162/153244304773633852

Número de citas: 16 (Web of Science) 32 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,8 (2020)
  • SJR: 1,691 (2004)
  • SNIP: 6,419 (2004)
  • Categorías SJR: Artificial Intelligence (Q1); Control and Systems Engineering (Q1); Software (Q1); Statistics and Probability (Q1)

Failure modeling and maintenance optimization for a railway line

  • Hokstad P.
  • Langseth H.
  • Lindqvist B.
  • Vatn J.

International Journal of Performability Engineering - 1/1/2005

Número de citas: 8 (Scopus)
  • CiteScore: 0,8 (2020)
  • Categorías SJR: Safety, Risk, Reliability and Quality

Latent classification models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/6/2005

10.1007/s10994-005-0472-5

Número de citas: 10 (Web of Science) 13 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,1 (2020)
  • SJR: 2,604 (2005)
  • SNIP: 5,656 (2005)
  • Categorías SJR: Artificial Intelligence (Q1); Software (Q1)

Competing risks for repairable systems: A data study

  • Langseth H.
  • Lindqvist B.

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

10.1016/j.jspi.2004.10.032

Número de citas: 33 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 1,4 (2020)
  • SJR: 0,937 (2006)
  • SNIP: 1,051 (2006)
  • Categorías SJR: Applied Mathematics (Q2); Statistics and Probability (Q2); Statistics, Probability and Uncertainty (Q2)

Classification using Hierarchical Naïve Bayes models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/5/2006

10.1007/s10994-006-6136-2

Número de citas: 47 (Web of Science) 62 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,1 (2020)
  • SJR: 1,8 (2006)
  • SNIP: 4,144 (2006)
  • Categorías SJR: Artificial Intelligence (Q1); Software (Q1)

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

Número de citas: 7 (Scopus)

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

  • Langseth H.

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

Número de citas: 14 (Scopus)

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

Número de citas: 11 (Scopus)
  • Categorías SJR: Statistics and Probability

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

Número de citas:
  • Dialnet
Open Access

Parallel importance sampling in conditional linear Gaussian networks

  • Salmerón A.
  • Ramos-López D.
  • Borchani H.
  • Martínez A.
  • Masegosa A.
  • Fernández A.
  • Langseth H.
  • Madsen A.
  • Nielsen T.
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Advances in Artificial Intelligence - 1/1/2015

10.1007/978-3-319-24598-0_4

Número de citas: 6 (Web of Science) 7 (Scopus)
  • Impacto Normalizado por Categoría: 0,767 (2015)
  • CiteScore: 1,8 (2020)
  • SJR: 0,369 (2015)
  • SNIP: 0,708 (2015)

Probability-based approach for predicting e-commerce consumer behaviour using sparse session data

  • Myklatun Ø.
  • Thorrud T.
  • Nguyen H.
  • Langseth H.
  • Kofod-Petersen A.

Proceedings of the International ACM Recommender Systems Challenge 2015 - 16/9/2015

10.1145/2813448.2813514

Número de citas:
  • Categorías SJR: Engineering (miscellaneous)
Open Access

d-VMP: Distributed Variational Message Passing

  • Andres Masegosa
  • Ana M. Martinez
  • Helge Langseth
  • Thomas Dyhre Nielsen
  • Antonio Salmerón
  • Darío Ramos-López
  • Anders Læsø Madsen
... Ver más Contraer

JMLR Workshop and Conference Proceedings - 1/1/2016

Número de citas: 8 (Scopus)
  • Factor Impacto JCR: 5 (2016)
  • CiteScore: 6,8 (2020)
  • SJR: 1,29 (2016)
  • SNIP: 2,222 (2016)
  • Impacto JCR a 5 años: 7,649
  • Categorías JCR: AUTOMATION & CONTROL SYSTEMS
Open Access

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

  • Salmerón A.
  • Madsen A.
  • Jensen F.
  • Langseth H.
  • Nielsen T.
  • Ramos-López D.
  • Martínez A.
  • Masegosa A.
... Ver más Contraer

ECAI 2016 - 1/1/2016

10.3233/978-1-61499-672-9-743

Número de citas:
  • Cuartil SJR: Q3
  • CiteScore: 0,6 (2020)
  • SJR: 0,202 (2016)
  • SNIP: 0,451 (2016)
  • Categorías SJR: Artificial Intelligence (Q3)
Open Access

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

  • Ramos-L pez D.o.
  • Salmer n A.
  • Rum R.
  • Mart nez A.M.
  • Nielsen T.D.
  • Masegosa A.R.
  • Langseth H.
  • Madsen A.L.
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Proceedings of the Eighth International Conference on Probabilistic Graphical Models - 1/1/2016

Número de citas:
  • Factor Impacto JCR: 5 (2016)
  • CiteScore: 6,8 (2020)
  • SJR: 1,29 (2016)
  • SNIP: 2,222 (2016)
  • Impacto JCR a 5 años: 7,649
  • Categorías JCR: AUTOMATION & CONTROL SYSTEMS

Financial Data Analysis with PGMs Using AMIDST

  • Cabanas R.
  • Martinez A.
  • Masegosa A.
  • Ramos-Lopez D.
  • Sameron A.
  • Nielsen T.
  • Langseth H.
  • Madsen A.
... Ver más Contraer

IEEE International Conference on Data Mining Workshops, ICDMW - 30/01/2017

10.1109/icdmw.2016.0185

Número de citas: 4 (Web of Science) 4 (Scopus)
  • Impacto Normalizado por Categoría: 0,586 (2017)
  • Categorías SJR: Computer Science Applications; Software
Open Access

Content-Based Social Recommendation with Poisson Matrix Factorization

  • da Silva E.
  • Langseth H.
  • Ramampiaro H.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 1/1/2017

10.1007/978-3-319-71249-9_32

Número de citas: 9 (Scopus)
  • CiteScore: 1,8 (2020)
  • SJR: 0,295 (2017)
  • SNIP: 0,673 (2017)

Bayesian models of data streams with Hierarchical Power Priors

  • Masegosa A.
  • Nielsen T.
  • Langseth H.
  • Ramos-López D.
  • Salmerón A.
  • Madsen A.

Proceedings of the 34th International Conference on Machine Learning - 1/1/2017

Número de citas: 2 (Scopus)
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

Número de citas: 1 (Scopus)
  • CiteScore: 0,8 (2020)
  • SJR: 0,167 (2017)
  • SNIP: 0,346 (2017)
  • Categorías SJR: Computer Science (miscellaneous)

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

Número de citas: 25 (Scopus)
  • Categorías SJR: Ocean Engineering

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Este autor no tiene informes ni otros tipos de publicaciones.

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 13

Última actualización de los datos: 18/05/24 9:32
Próxima recolección programada: 25/05/24 3:00