Focussed Bayesian fusion is a local Bayesian fusion technique by that high costs caused by Bayesian fusion can get circumvented. This publication addresses globally optimal decision making on the basis of a focussed Bayesian model. Therefore, common decision criteria under linear partial information and in particular principles of lazy decision making are applied. We also present an interval scheme for global posterior probabilities whose informativeness is notably high
We present a unifying framework for the global optimization of functions which are expensive to eval...
Bayesian theory delivers a powerful theoretical platform for the mathematical description and execut...
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state...
Information fusion is essential for the retrieval of desired information in a sufficiently precise, ...
This paper proposes a new method for solving Bayesian decision problems. The method con-sists of rep...
We present local Bayesian fusion approaches for the reduction of storage and computational costs of ...
Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusi...
Abstract-We consider the problem of fusing local decision outputs into a global decision with a budg...
In fusing heterogeneous information sources, their different abstraction levels and formalizations h...
This paper develops a mathematical and computational framework for analyzing the expected perfor-man...
Abstract: In the field of reconnaissance and in many other real world applications, information from...
Sequential Bayesian information fusion is a process in which streams of observations from multiple s...
Abstract — Many problems involve joint decision and estima-tion, where qualities of decision and est...
We present a unifying framework for the global optimization of functions which are expensive to eval...
Bayesian statistics leads to a powerful fusion methodology, especially for the fusion of heterogeneo...
We present a unifying framework for the global optimization of functions which are expensive to eval...
Bayesian theory delivers a powerful theoretical platform for the mathematical description and execut...
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state...
Information fusion is essential for the retrieval of desired information in a sufficiently precise, ...
This paper proposes a new method for solving Bayesian decision problems. The method con-sists of rep...
We present local Bayesian fusion approaches for the reduction of storage and computational costs of ...
Local Bayesian fusion approaches aim to reduce high storage and computational costs of Bayesian fusi...
Abstract-We consider the problem of fusing local decision outputs into a global decision with a budg...
In fusing heterogeneous information sources, their different abstraction levels and formalizations h...
This paper develops a mathematical and computational framework for analyzing the expected perfor-man...
Abstract: In the field of reconnaissance and in many other real world applications, information from...
Sequential Bayesian information fusion is a process in which streams of observations from multiple s...
Abstract — Many problems involve joint decision and estima-tion, where qualities of decision and est...
We present a unifying framework for the global optimization of functions which are expensive to eval...
Bayesian statistics leads to a powerful fusion methodology, especially for the fusion of heterogeneo...
We present a unifying framework for the global optimization of functions which are expensive to eval...
Bayesian theory delivers a powerful theoretical platform for the mathematical description and execut...
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state...