Langseth, Helge Author

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)

Classification using Hierarchical Naïve Bayes models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/5/2006

10.1007/s10994-006-6136-2

Cite count: 47 (Web of Science) 62 (Scopus)

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

Cite count: 33 (Scopus)
Open Access

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

  • Vassøy B.
  • Langseth H.

Artificial Intelligence Review - 1/4/2024

10.1007/s10462-023-10663-5

Cite count:

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

Cite count: 25 (Scopus)

Deep Contextual Grid Triplet Network for Context-Aware Recommendation

  • Sofia Aftab
  • Heri Ramampiaro
  • Helge Langseth
  • Massimiliano Ruocco

IEEE Access - 1/1/2023

10.1109/access.2023.3310470

Cite count:

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

  • Pitsilis G.
  • Ramampiaro H.
  • Langseth H.

APPLIED INTELLIGENCE - 1/12/2018

10.1007/s10489-018-1242-y

Cite count: 67 (Scopus)

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

Cite count: 8 (Scopus)

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:
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

Cite count: 16 (Web of Science) 32 (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)

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)

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)

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

A hybrid CBR and BN architecture refined through data analysis

  • Bruland T.
  • Aamodt A.
  • Langseth H.

International Conference on Intelligent Systems Design and Applications, ISDA - 1/12/2011

10.1109/isda.2011.6121773

Cite count: 4 (Scopus)
Open Access

A new method for vertical parallelisation of TAN learning based on balanced incomplete block designs

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

Proceedings of the 7th European Workshop on Probabilistic Graphical Models - 1/1/2014

10.1007/978-3-319-11433-0_20

Cite count: 9 (Web of Science) 10 (Scopus)
Open Access

Architectures integrating case-based reasoning and Bayesian networks for clinical decision support

  • Bruland T.
  • Aamodt A.
  • Langseth H.

IFIP Advances in Information and Communication Technology - 1/1/2010

10.1007/978-3-642-16327-2-13

Cite count: 17 (Scopus)
Open Access

Bayesian Exploration in Deep Reinforcement Learning

  • Killingberg L.
  • Langseth H.

CEUR Workshop Proceedings - 1/1/2023

Cite count:

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

Cite count: 2 (Scopus)

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

  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/12/2013

10.3233/978-1-61499-330-8-165

Cite count: 5 (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

Cite count: 2 (Scopus)
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

Cite count: 9 (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

Cite count: 1 (Scopus)

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 - 2022

10.5220/0010991800003116

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