Abstract—Computing the partition function and the marginals of a global probability distribution are two important issues in any probabilistic inference problem. In a previous work, we presented sub-tree based upper and lower bounds on the partition function of a given probabilistic inference problem. Using the entropies of the sub-trees we proved an inequality that compares the lower bounds obtained from different sub-trees. In this paper we investigate the properties of one specific lower bound, namely the lower bound computed by the minimum entropy sub-tree. We also investigate the relationship between the minimum entropy sub-tree and the sub-tree that gives the best lower bound. I
Abstract—Upper and lower bounds are obtained for the joint entropy of a collection of random variabl...
The estimation of categorical distributions under marginal constraints summarizing some sample from ...
It is well known that the entropy H(X) of a finite random variable is always greater or equal to the...
We introduce a novel method for estimating the partition function and marginals of distributions def...
It is well known that the entropy H(X) of a discrete random variable X is always greater than or equ...
It is well known that the entropy H(X) of a discrete random variable X is always greater than or equ...
Abstract — The differential entropy is a quantity employed ubiquitously in communications, statistic...
Abstract — The differential entropy is a quantity employed ubiquitously in communications, statistic...
In this thesis, we give a new class of outer bounds on the marginal polytope, and propose a cutting-...
In probability theory, Bayesian statistics, artificial intelligence and database theory the minimum ...
This paper is part of a general study of efficient information selection, storage and processing. It...
The combination of mathematical models and uncertainty measures can be applied in the area of data m...
The importance of finding minimum entropy probability distributions and the value of minimum entropy...
summary:In probability theory, Bayesian statistics, artificial intelligence and database theory the ...
AbstractThe power of probabilistic linear decision trees is examined. It is shown that the standard ...
Abstract—Upper and lower bounds are obtained for the joint entropy of a collection of random variabl...
The estimation of categorical distributions under marginal constraints summarizing some sample from ...
It is well known that the entropy H(X) of a finite random variable is always greater or equal to the...
We introduce a novel method for estimating the partition function and marginals of distributions def...
It is well known that the entropy H(X) of a discrete random variable X is always greater than or equ...
It is well known that the entropy H(X) of a discrete random variable X is always greater than or equ...
Abstract — The differential entropy is a quantity employed ubiquitously in communications, statistic...
Abstract — The differential entropy is a quantity employed ubiquitously in communications, statistic...
In this thesis, we give a new class of outer bounds on the marginal polytope, and propose a cutting-...
In probability theory, Bayesian statistics, artificial intelligence and database theory the minimum ...
This paper is part of a general study of efficient information selection, storage and processing. It...
The combination of mathematical models and uncertainty measures can be applied in the area of data m...
The importance of finding minimum entropy probability distributions and the value of minimum entropy...
summary:In probability theory, Bayesian statistics, artificial intelligence and database theory the ...
AbstractThe power of probabilistic linear decision trees is examined. It is shown that the standard ...
Abstract—Upper and lower bounds are obtained for the joint entropy of a collection of random variabl...
The estimation of categorical distributions under marginal constraints summarizing some sample from ...
It is well known that the entropy H(X) of a finite random variable is always greater or equal to the...