Best entropy estimation is a technique that has been widely applied in many areas of science. It consists of estimating an unknown density from some of its moments by maximizing some measure of the entropy of the estimate. This problem can be modelled as a partially-finite convex program, with an integrable function as the variable. A complete duality and existence theory is developed for this problem and for an associated extended problem which allows singular, measure-theoretic solutions. This theory explains the appearance of singular components observed in the literature when the Burg entropy is used. It also provides a unified treatment of existence conditions when the Burg, Boltzmann-Shannon, or some other entropy is used as the objec...
In this paper, we focus on the combination of probabilistic logic programming with the principle of ...
This paper shows the equivalence of entropy-maximization models to geometric programs. As a result w...
In this paper, we focus on the combination of probabilistic logic programming with the principle of...
Abstract. Best entropy estimation is a technique that has been widely applied in many areas of scien...
This article revisits the maximum entropy algorithm in the context of recovering the probability dis...
A necessary and sufficient condition for the existence of the maximum entropy (ME) function defined ...
In many practical situations, we have only partial information about the probabilities. In some case...
We consider the problem of estimating a probability distribution that maximizes the entropy while sa...
The finite moment problem in the framework of maximum entropy approach is numerically investigated t...
We consider the problem of estimating a probability distribution that maximizes the entropy while sa...
International audienceIn this paper, we study entropy maximisation problems in order to reconstruct ...
We describe an algorithm to efficiently compute maximum entropy densities, i.e. densities maximizing...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
Abstract: One of the important issues among many information measures is Shannon (1948) entropy. In ...
A class of algorithms for approximation of the maximum entropy estimate of probability density func...
In this paper, we focus on the combination of probabilistic logic programming with the principle of ...
This paper shows the equivalence of entropy-maximization models to geometric programs. As a result w...
In this paper, we focus on the combination of probabilistic logic programming with the principle of...
Abstract. Best entropy estimation is a technique that has been widely applied in many areas of scien...
This article revisits the maximum entropy algorithm in the context of recovering the probability dis...
A necessary and sufficient condition for the existence of the maximum entropy (ME) function defined ...
In many practical situations, we have only partial information about the probabilities. In some case...
We consider the problem of estimating a probability distribution that maximizes the entropy while sa...
The finite moment problem in the framework of maximum entropy approach is numerically investigated t...
We consider the problem of estimating a probability distribution that maximizes the entropy while sa...
International audienceIn this paper, we study entropy maximisation problems in order to reconstruct ...
We describe an algorithm to efficiently compute maximum entropy densities, i.e. densities maximizing...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
Abstract: One of the important issues among many information measures is Shannon (1948) entropy. In ...
A class of algorithms for approximation of the maximum entropy estimate of probability density func...
In this paper, we focus on the combination of probabilistic logic programming with the principle of ...
This paper shows the equivalence of entropy-maximization models to geometric programs. As a result w...
In this paper, we focus on the combination of probabilistic logic programming with the principle of...