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Towards Distributed Bayesian Estimation A Short Note on Selected Aspects
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SYSNO ASEP 0368319 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Towards Distributed Bayesian Estimation A Short Note on Selected Aspects Author(s) Dedecius, Kamil (UTIA-B) RID, ORCID
Sečkárová, Vladimíra (UTIA-B) RIDNumber of authors 2 Source Title The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011). - Prague : Institute of Information Theory and Automation, 2011 - ISBN 978-80-903834-6-3 Pages s. 67-72 Number of pages 6 s. Action The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011) Event date 16.12.2011-16.12.2011 VEvent location Sierra Nevada Country ES - Spain Event type WRD Language eng - English Country CZ - Czech Republic Keywords efficient estimation ; a linear or nonlinear model ; distributed estimation ; Bayesian decision making Subject RIV BB - Applied Statistics, Operational Research R&D Projects GA102/08/0567 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation The rapid development of ad-hoc wireless networks, sensor networks and similar calls for efficient estimation of common parameters of a linear or nonlinear model used to describe the operating environment. Therefore, the theory of collaborative distributed estimation has attained a very considerable focus in the past decade, however, mostly in the classical deterministic realm. We conjecture, that the consistent and versatile Bayesian decision making framework, whose applications range from the basic probability counting up to the nonlinear estimation theory, can significantly contribute to the distributed estimation theory. The limited extent of the paper allows to address the considered problem only very superficially and shortly. Therefore, we are forced to leave the rigorous approach in favor of a short survey indicating the arising possibilities appealing to the non- Bayesian literature. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2012
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