Helge Langseth

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón: Mixtures of truncated basis functions. Int. J. Approx. Reasoning 53(2): 212-227 (2012)

Helge Langseth, Thomas Dyhre Nielsen: A latent model for collaborative filtering. Int. J. Approx. Reasoning 53(4): 447-466 (2012)

Tore Bruland, Agnar Aamodt, Helge Langseth: A hybrid CBR and BN architecture refined through data analysis. ISDA 2011: 906-913

Tor Gunnar Houeland, Tore Bruland, Agnar Aamodt, Helge Langseth: Extended Abstract: Combining CBR and BN using metareasoning. SCAI 2011: 189-190

Terje N. Lillegraven, Arnt C. Wolden, Anders Kofod-Petersen, Helge Langseth: Extended Abstract: A design for a tourist CF system. SCAI 2011: 193-194

Anders Kofod-Petersen, Fredrik Heintz, Helge Langseth (Eds.): Eleventh Scandinavian Conference on Artificial Intelligence, SCAI 2011, Trondheim, Norway, May 24th - 26th, 2011. Frontiers in Artificial Intelligence and Applications 227, IOS Press 2011, isbn 978-1-60750-753-6

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón: Parameter estimation and model selection for mixtures of truncated exponentials. Int. J. Approx. Reasoning 51(5): 485-498 (2010)

Shengtong Zhong, Ana M. Martínez, Thomas D. Nielsen, Helge Langseth: Towards a More Expressive Model for Dynamic Classification. FLAIRS Conference 2010

Tore Bruland, Agnar Aamodt, Helge Langseth: Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. Intelligent Information Processing 2010: 82-91

Helge Langseth, Thomas D. Nielsen: Latent classification models for binary data. Pattern Recognition 42(11): 2724-2736 (2009)

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón: Inference in hybrid Bayesian networks. Rel. Eng. & Sys. Safety 94(10): 1499-1509 (2009)

Helge Langseth, Thomas D. Nielsen, Rafael Rumí, Antonio Salmerón: Maximum Likelihood Learning of Conditional MTE Distributions. ECSQARU 2009: 240-251

Helge Langseth, Luigi Portinale: Bayesian networks in reliability. Rel. Eng. & Sys. Safety 92(1): 92-108 (2007)

Helge Langseth, Thomas D. Nielsen: Classification using Hierarchical Naïve Bayes models. Machine Learning 63(2): 135-159 (2006)

Helge Langseth, Thomas D. Nielsen: Latent Classification Models. Machine Learning 59(3): 237-265 (2005)

Helge Langseth, Thomas D. Nielsen: Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains. Journal of Machine Learning Research 4: 339-368 (2003)

Finn Verner Jensen, Uffe Kjærulff, Brian Kristiansen, Helge Langseth, Claus Skaanning, Jirí Vomlel, Marta Vomlelová: The SACSO methodology for troubleshooting complex systems. AI EDAM 15(4): 321-333 (2001)

Helge Langseth, Olav Bangsø: Parameter Learning in Object-Oriented Bayesian Networks. Ann. Math. Artif. Intell. 32(1-4): 221-243 (2001)

Olav Bangsø, Helge Langseth, Thomas D. Nielsen: Structural Learning in Object Oriented Domains. FLAIRS Conference 2001: 340-344

Helge Langseth, Finn Verner Jensen: Heuristics for Two Extensions of Basic Troubleshooting. SCAI 2001: 80-89