
Likelihoods and Parameter Priors for Bayesian Networks
We develop simple methods for constructing likelihoods and parameter pri...
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Dependence and Relevance: A probabilistic view
We examine three probabilistic concepts related to the sentence "two var...
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Random Algorithms for the Loop Cutset Problem
We show how to find a minimum loop cutset in a Bayesian network with hig...
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Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997)
This is the Proceedings of the Thirteenth Conference on Uncertainty in A...
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On the Logic of Causal Models
This paper explores the role of Directed Acyclic Graphs (DAGs) as a repr...
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dSeparation: From Theorems to Algorithms
An efficient algorithm is developed that identifies all independencies i...
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Separable and transitive graphoids
We examine three probabilistic formulations of the sentence a and b are ...
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Advances in Probabilistic Reasoning
This paper discuses multiple Bayesian networks representation paradigms ...
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An Entropybased Learning Algorithm of Bayesian Conditional Trees
This article offers a modification of Chow and Liu's learning algorithm ...
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Inference Algorithms for Similarity Networks
We examine two types of similarity networks each based on a distinct not...
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Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe algorithms for learning Bayesian networks from a combination...
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On Testing Whether an Embedded Bayesian Network Represents a Probability Model
Testing the validity of probabilistic models containing unmeasured (hidd...
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Learning Gaussian Networks
We describe algorithms for learning Bayesian networks from a combination...
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Approximation Algorithms for the Loop Cutset Problem
We show how to find a small loop curser in a Bayesian network. Finding s...
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Asymptotic Model Selection for Directed Networks with Hidden Variables
We extend the Bayesian Information Criterion (BIC), an asymptotic approx...
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A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees
An algorithm is developed for finding a close to optimal junction tree o...
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Graphical Models and Exponential Families
We provide a classification of graphical models according to their repre...
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Quantifier Elimination for Statistical Problems
Recent improvement on Tarski's procedure for quantifier elimination in t...
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Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
We show that the only parameter prior for complete Gaussian DAG models t...
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Likelihood Computations Using Value Abstractions
In this paper, we use evidencespecific value abstraction for speeding B...
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Perfect TreeLike Markovian Distributions
We show that if a strictly positive joint probability distribution for a...
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Asymptotic Model Selection for Naive Bayesian Networks
We develop a closed form asymptotic formula to compute the marginal like...
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Factorization of Discrete Probability Distributions
We formulate necessary and sufficient conditions for an arbitrary discre...
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Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models
We present and implement two algorithms for analytic asymptotic evaluati...
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A DistanceBased Branch and Bound Feature Selection Algorithm
There is no known efficient method for selecting k Gaussian features fro...
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Dan Geiger
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Professor of Computer Science, Technion  Israel Institute of Technology