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09/26/2013
Approximate Kalman Filter Q-Learning for Continuous State-Space MDPs
We seek to learn an effective policy for a Markov Decision Process (MDP)...
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03/27/2013
Intelligent Probabilistic Inference
The analysis of practical probabilistic models on the computer demands a...
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03/27/2013
DAVID: Influence Diagram Processing System for the Macintosh
Influence diagrams are a directed graph representation for uncertainties...
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03/27/2013
A Backwards View for Assessment
Much artificial intelligence research focuses on the problem of deducing...
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03/27/2013
Efficient Inference on Generalized Fault Diagrams
The generalized fault diagram, a data structure for failure analysis bas...
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03/27/2013
A Heuristic Bayesian Approach to Knowledge Acquisition: Application to Analysis of Tissue-Type Plasminogen Activator
This paper describes a heuristic Bayesian method for computing probabili...
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03/27/2013
A Linear Approximation Method for Probabilistic Inference
An approximation method is presented for probabilistic inference with co...
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03/27/2013
Simulation Approaches to General Probabilistic Inference on Belief Networks
A number of algorithms have been developed to solve probabilistic infere...
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03/27/2013
Evidence Absorption and Propagation through Evidence Reversals
The arc reversal/node reduction approach to probabilistic inference is e...
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03/27/2013
Directed Reduction Algorithms and Decomposable Graphs
In recent years, there have been intense research efforts to develop eff...
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03/20/2013
A Graph-Based Inference Method for Conditional Independence
The graphoid axioms for conditional independence, originally described b...
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03/13/2013
Decision Making Using Probabilistic Inference Methods
The analysis of decision making under uncertainty is closely related to ...
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03/13/2013
Structural Controllability and Observability in Influence Diagrams
Influence diagram is a graphical representation of belief networks with ...
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03/06/2013
Using Potential Influence Diagrams for Probabilistic Inference and Decision Making
The potential influence diagram is a generalization of the standard "con...
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03/06/2013
Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties
Problems of probabilistic inference and decision making under uncertaint...
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03/06/2013
End-User Construction of Influence Diagrams for Bayesian Statistics
Influence diagrams are ideal knowledge representations for Bayesian stat...
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02/27/2013
Global Conditioning for Probabilistic Inference in Belief Networks
In this paper we propose a new approach to probabilistic inference on be...
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02/27/2013
Three Approaches to Probability Model Selection
This paper compares three approaches to the problem of selecting among p...
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02/27/2013
A Decision-Based View of Causality
Most traditional models of uncertainty have focused on the associational...
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02/27/2013
Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables
Laplace's method, a family of asymptotic methods used to approximate int...
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01/30/2013
Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)
One of the benefits of belief networks and influence diagrams is that so...
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01/30/2013
Learning From What You Don't Observe
The process of diagnosis involves learning about the state of a system f...
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01/23/2013
Efficient Value of Information Computation
One of the most useful sensitivity analysis techniques of decision analy...
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06/13/2012
Sensitivity analysis in decision circuits
Decision circuits have been developed to perform efficient evaluation of...
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03/15/2012
Dynamic programming in in uence diagrams with decision circuits
Decision circuits perform efficient evaluation of influence diagrams, bu...
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03/15/2012
Three new sensitivity analysis methods for influence diagrams
Performing sensitivity analysis for influence diagrams using the decisio...
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02/14/2012