I’m an associate professor in computer science at the Norwegian university of science and technology (NTNU). Currently, my research interest lies in similarity search and metric indexing. (See also my listing in Cristin. Note that the Cristing listing contains duplicates.)
Mujahed Eleyat, Dag Haugland, Magnus Lie Hetland and Lasse Natvig. “Parallel algorithms for the maximum flow problem with minimum lot sizes”. To appear in Proceedings of the International Conference in Operations Research (OR), Springer, 2011.
Magnus Lie Hetland. Ptolemaic Indexing. arXiv:0911.4384 [cs.DS].
Dag Haugland, Mujahed Eleyat and Magnus Lie Hetland, The maximum flow problem with minimum lot sizes. In Lecture Notes in Computer Science Vol. 6971, pp. 170—182, 2011.
Jakub Lokoc, Magnus Lie Hetland, Tomas Skopal and Christian Beecks, “Ptolemaic Indexing of the Signature Quadratic Form Distance”. In Proceedings of the Fourth International Conference on Similarity Search and Applications (SISAP), June 30-July 1, 2011, Lipary, Italy. Best paper. (Presentation)
Svein Erik Bratsberg and Magnus Lie Hetland. Dynamic Optimization of Queries in Pivot-Based Indexing. Multimedia Tools and Applications, 2010.
Ole Edsberg and Magnus Lie Hetland. Indexing Inexact Proximity Search with Distance Regression in Pivot Space. In Proceedings of the Third International Conference on SImilarity Search and Applications (SISAP), ACM, 2010. Best paper.
Nils Grimsmo, Truls Amundsen Bjørklund and Magnus Lie Hetland. Linear Computation of the Maximum Simultaneous Forward and Backward Bisimulation for Node-Labeled Trees. In Proceedings of the 7th International XML Database Symposium on Database and XML Technologies (XSym), 2010. (Extended version.)
Nils Grimsmo, Truls Amundsen Bjørklund and Magnus Lie Hetland. Fast Optimal Twig Joins. Proceedings of the 36th international conference on Very Large Data Bases (VLDB), 2010.
Magnus Lie Hetland. The Basic Principles of Metric Indexing. In Carlos A. Coello Coello, Satchidananda Dehuri and Susmita Ghosh, editors, Swarm Intelligence for Multi-objective Problems in Data Mining, Springer-Verlag, 2009. (Version with notes inline. The original publication is available at www.springerlink.com.)
Will Archer Arentz, Magnus Lie Hetland and Bjørn Olstad. Methods for retrieving musical information based on rhythm and pitch correlations. In Journal of New Music Research 34(2), 2005.
Magnus Lie Hetland and Pål Sætrom. Evolutionary Rule Mining in Time Series Databases. In Machine Learning, 58(2). Kluwer Academic Publishers, 2005.
Magnus Lie Hetland. A survey of recent methods for efficient retrieval of similar time sequences. In Mark Last, Abraham Kandel, and Horst Bunke, editors, Data Mining in Time Series Databases. World Scientific, 2004.
Magnus Lie Hetland and Pål Sætrom. Temporal rule discovery using genetic programming and specialized hardware. In Ahmad Lotfi, Jonathon M. Garibaldi, editors, Applications and Science in Soft Computing, Springer-Verlag, 2004.
Magnus Lie Hetland and Pål Sætrom. A Comparison of Hardware and Software in Sequence Rule Evolution. In Proc. 8th Scandinavian Conf. on Artificial Intelligence, SCAI, IOS Press, 2003.
Pål Sætrom and Magnus Lie Hetland. Multiobjective Evolution of Temporal Rules. In Proc. 8th Scandinavian Conf. on Artificial Intelligence, SCAI, IOS Press, 2003.
Amund Tveit, Magnus Lie Hetland and Håvard Engum. Incremental and Decremental Proximal Support Vector Classification using Decay Coefficients. In Proc. 5th Int. Conf. on Data Warehousing and Knowledge Discovery, DaWaK, Springer-Verlag, 2003.
Amund Tveit and Magnus Lie Hetland. Multicategory Incremental Proximal Support Vector Classifiers. In Proc. 7th Int. Conf. on Knowledge-Based Intelligent Information & Engineering Systems, KES, Springer-Verlag, 2003.
Magnus Lie Hetland and Pål Sætrom. The Role of Discretization Parameters in Sequence Rule Evolution. In Proc. 7th Int. Conf. on Knowledge-Based Intelligent Information & Engineering Systems, KES, Springer-Verlag, 2003.
Pål Sætrom and Magnus Lie Hetland. Unsupervised Temporal Rule Mining with Genetic Programming and Specialized Hardware. In Proc. 2003 Int. Conf. on Machine Learning and Applications, ICMLA, Association for Machine Learning and Applications, 2003.
Magnus Lie Hetland and Pål Sætrom. Temporal rule discovery using genetic programming and specialized hardware. In Proc. 4th Int. Conf. on Recent Advances in Soft Computing, RASC, 2002.
Magnus Lie Hetland. Python Algorithms (316 p). Apress, 2010.
Magnus Lie Hetland. Beginning Python, 2nd ed (656 p). Apress, 2008.
Magnus Lie Hetland. Beginning Python (604 p). Apress, 2005.
Magnus Lie Hetland. Practical Python (648 p). Apress, 2002.
Bilegsaikhan Naidan, Magnus Lie Hetland and Ole Edsberg, “Approximate similarity search using samples”, The International Conference on Similarity Search and Applications (SISAP), June 30-July 1, 2011, Lipary, Italy.
Rune Johan Hovland, Anne C. Elster and Magnus Lie Hetland, “High Data Volumes and Streaming on Future GPU Systems”, The Eighth Annual Meeting on High Performance Computing and Infrastructure in Norway (NOTUR), May 18-20, 2009, Trondheim, Norway.
Appearance on Newton, a popular science show for children on NRK (Jan 10, 2010), explaining how search engines work. (Dept. news story)
The Teacher of the Year award at the Faculty of Information Technology, Mathematics and Electrical Engineering, NTNU, 2009.
I’ve been a reviewer for the following publications and conferences:
Proc. of the 28th International Conference on Data Engineering, ICDE, 2012.
Proc. Scandinavian Conference on Artificial Intelligence, SCAI, 2006, 2008, 2011.
ACM International Conference on Computing Frontiers, CF, 2011.
Proc. Norwegian Informatics Conference, NIK, 2004, 2006, 2007, 2008, 2009.
Proc. of the IASTED International Conference on Artificial Intelligence and Applications, AIA, 2007.
Software: Practice and Experience, Wiley InterScience, 2006.
IEEE Trans. on Pattern Analysis and Machine Intelligence, TPAMI, 2006.
Proc. Int. Conf. of Computational Intelligence and Multimedia Applications, ICCIMA, IEEE CS Press, 2005.
Proc. Int. Conf. on Machine Learning and Data Mining, MLDM, Springer-Verlag, 2005.
Machine Learning, 58(2), Kluwer Academic Publishers, 2005.
Proc. 19th ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, OOPSLA, ACM 2004.