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Regime Aware Learning
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-8678-1164
2016 (English)In: Proceedings of the Eighth International Conference on Probabilistic Graphical Models, JMLR , 2016, Vol. 52, 1-12 p.Conference paper (Refereed)
Abstract [en]

We propose a regime aware learning algorithm to learn a sequence of Bayesian networks (BNs) that model a system that undergoes regime changes. The last BN in the sequence represents the system’s current regime, and should be used for BN inference. To explore the feasibility of the algorithm, we create baseline tests against learning a singe BN, and show that our proposed algorithm outperforms the single BN approach. We also apply the learning algorithm on real world data from the financial domain, where it is evident that the algorithm is able to produce BNs that have adapted to the regime changes during the most recent global financial crisis of 2007-08.

Place, publisher, year, edition, pages
JMLR , 2016. Vol. 52, 1-12 p.
, JMLR: Workshop and Conference Proceedings, ISSN 1938-7228 ; 52
Keyword [en]
Regime changes, Bayesian networks, financial application
National Category
Computer and Information Science
URN: urn:nbn:se:liu:diva-131133OAI: diva2:968120
Eighth International Conference on Probabilistic Graphical Models (PGM 2016), Lugano, Switzerland, September 6-9, 2016
Available from: 2016-09-12 Created: 2016-09-12 Last updated: 2016-09-19Bibliographically approved

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Bendtsen, Marcus
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Database and information techniquesFaculty of Science & Engineering
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