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56,074
Approximating discrete probability distributions with dependence trees
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1968
"... A method is presented to approximate optimally an ndimensional discrete probability distribution by a product of secondorder distributions, or the distribution of the firstorder tree dependence. The problem is to find an optimum set of n1 first order dependence relationship among the n variables ..."
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Cited by 881 (0 self)
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A method is presented to approximate optimally an ndimensional discrete probability distribution by a product of secondorder distributions, or the distribution of the firstorder tree dependence. The problem is to find an optimum set of n1 first order dependence relationship among the n
Factorization of Discrete Probability Distributions
 UAI 2002
, 2002
"... We formulate necessary and sufficient conditions for an arbitrary discrete probability distribution to factor according to an undirected graphical model, or a loglinear model, or other more general exponential models. This result generalizes the well known HammersleyClifford Theorem. ..."
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We formulate necessary and sufficient conditions for an arbitrary discrete probability distribution to factor according to an undirected graphical model, or a loglinear model, or other more general exponential models. This result generalizes the well known HammersleyClifford Theorem.
QUANTIZATION OF DISCRETE PROBABILITY DISTRIBUTIONS
"... We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex. Such setting yields precise asymptotic characterization i ..."
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Cited by 1 (1 self)
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We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex. Such setting yields precise asymptotic characterization
An Algorithm for Quantization of Discrete Probability Distributions
"... We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex, yielding precise characterization in the highrate regime ..."
Abstract

Cited by 4 (0 self)
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We study the problem of quantization of discrete probability distributions, arising in universal coding, as well as other applications. We show, that in many situations this problem can be reduced to the covering problem for the unit simplex, yielding precise characterization in the high
Discrete Probability Distribution of Retrieval Times
"... Abstract. This paper discusses a method for pricing the storage of inbound containers in a container yard. The pricing structure is characterized by a freetimelimit and a storage price for the storage time that extends beyond the freetimelimit. A cost model is developed from the viewpoint of a p ..."
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public terminal operator as well as a private terminal operator. Unlike a previous study on this issue, this study assumes that the retrieval times follow a discrete probability distribution, which is more realistic than the previous study. A solution procedure is suggested and illustrated by using
Automatic verification of realtime systems with discrete probability distributions
 Theoretical Computer Science
, 1999
"... Abstract. We consider the timed automata model of [3], which allows the analysis of realtime systems expressed in terms of quantitative timing constraints. Traditional approaches to realtime system description express the model purely in terms of nondeterminism; however, we may wish to express the ..."
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Cited by 118 (33 self)
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the likelihood of the system making certain transitions. In this paper, we present a model for realtime systems augmented with discrete probability distributions. Furthermore, using the algorithm of [5] with fairness, we develop a model checking method for such models against temporal logic properties which can
Approximating Discrete Probability Distributions With Bayesian Networks
 in Proceedings of the International Conference on Artificial Intelligence in Science and Technology
, 2000
"... I generalise the arguments of [Chow & Liu 1968] to show that a Bayesian network satisfying some arbitrary constraint that best approximates a probability distribution is one for which mutual information weight is maximised. I give a practical procedure for nding an approximation network and e ..."
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Cited by 12 (3 self)
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I generalise the arguments of [Chow & Liu 1968] to show that a Bayesian network satisfying some arbitrary constraint that best approximates a probability distribution is one for which mutual information weight is maximised. I give a practical procedure for nding an approximation network
Consider a univariate discrete probability distribution of
"... ( airgap standard by eithe Account and cres recomm method, as sum o storm su unreason by obse and stor level cal is more crest an ..."
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( airgap standard by eithe Account and cres recomm method, as sum o storm su unreason by obse and stor level cal is more crest an
On the use of sparsity for recovering discrete probability distributions from their moments
 Statistical Signal Processing Workshop (SSP), 2011 IEEE
"... ABSTRACT We address the problem of determining the probability distribution of a discrete random variable from its moments, using a sparsitybased approach. If the random variable can take at most K different values from a potential set of M K values, then its moments can be represented as linear m ..."
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Cited by 2 (0 self)
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ABSTRACT We address the problem of determining the probability distribution of a discrete random variable from its moments, using a sparsitybased approach. If the random variable can take at most K different values from a potential set of M K values, then its moments can be represented as linear
Results 1  10
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56,074