A useful technique in underdetermined inverse problems is that of maximum entropy. A simple error bound for averages over a distribution approximated by the maximum entropy method in the case of the undetermined Hausdorff moment problem was devised. Under the conditions specified, the error bound for averages over such an approximate distribution can be very tight. Numerical examples to illustrate are presented
In this paper, we consider a special nonlinear expectation problem on the special parameter space an...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
A useful technique in underdetermined inverse problems is that of maximum entropy. A simple error bo...
The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This ...
The recovering of a positive density function of which a finite number of moments are assigned is co...
The maximum entropy method was originally proposed as a variational technique to determine probabili...
A class of algorithms for approximation of the maximum entropy estimate of probability density func...
The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This ...
In many practical situations, we have only partial information about the probabilities. In some case...
The maximum entropy method for the Hausdorff moment problem suffers from ill conditioning as it uses...
There are two entropy-based methods to deal with linear inverse problems, which we shall call the or...
International audienceWe consider the linear inverse problem of reconstructing an unknown finite mea...
ABSTRACT. We propose an information-theoretic approach to approximate asymptotic distributions of st...
AbstractWe consider the linear inverse problem of reconstructing an unknown finite measure μ from a ...
In this paper, we consider a special nonlinear expectation problem on the special parameter space an...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
A useful technique in underdetermined inverse problems is that of maximum entropy. A simple error bo...
The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This ...
The recovering of a positive density function of which a finite number of moments are assigned is co...
The maximum entropy method was originally proposed as a variational technique to determine probabili...
A class of algorithms for approximation of the maximum entropy estimate of probability density func...
The maximum entropy principle is a powerful tool for solving underdetermined inverse problems. This ...
In many practical situations, we have only partial information about the probabilities. In some case...
The maximum entropy method for the Hausdorff moment problem suffers from ill conditioning as it uses...
There are two entropy-based methods to deal with linear inverse problems, which we shall call the or...
International audienceWe consider the linear inverse problem of reconstructing an unknown finite mea...
ABSTRACT. We propose an information-theoretic approach to approximate asymptotic distributions of st...
AbstractWe consider the linear inverse problem of reconstructing an unknown finite measure μ from a ...
In this paper, we consider a special nonlinear expectation problem on the special parameter space an...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
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