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Bayesian approximation and invariance of Bayesian belief functions

DSpace at IIT Bombay

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Title Bayesian approximation and invariance of Bayesian belief functions
 
Creator JOSHI, AV
SAHASRABUDHE, SC
SHANKAR, K
 
Subject dempster-shafer theory
 
Description The Dempster-Shafer theory is being applied for handling uncertainty in various domains. Many methods have been suggested in the literature for faster computation of belief which is otherwise exponentially complex. Bayesian approximation is one such method. In this paper, we first present some results on invariance of Bayesian belief functions under Dempster's combination rule. Based on this, we interpret Bayesian approximation and further show that it inherits these properties from the combination operator of Dempster's combination rule. Finally, we bring into focus the limitation of Bayesian approximation.
 
Publisher SPRINGER-VERLAG BERLIN
 
Date 2011-10-23T11:07:06Z
2011-12-15T09:11:07Z
2011-10-23T11:07:06Z
2011-12-15T09:11:07Z
1995
 
Type Article; Proceedings Paper
 
Identifier SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING AND UNCERTAINTY,946,251-258
3-540-60112-0
http://dspace.library.iitb.ac.in/xmlui/handle/10054/15112
http://hdl.handle.net/100/1866
 
Source European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU 95),FRIBOURG, SWITZERLAND,JUL 03-05, 1995
 
Language English