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    UAI
    1994
    130views Artificial Intelligence» more  UAI 1994»
    Global Conditioning for Probabilistic Inference in Belief Networks
    14 years 1 months ago
    Global Conditioning for Probabilistic Inference in Belief Networks
    Download  www.stanford.edu
    In this paper we propose a new approach to probabilistic inference on belief networks, global conditioning, which is a simple generalization of Pearl's (1986b) method of loop...
    Ross D. Shachter, Stig K. Andersen, Peter Szolovit...
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    UAI
    1994
    73views Artificial Intelligence» more  UAI 1994»
    Three Approaches to Probability Model Selection
    14 years 1 months ago
    Three Approaches to Probability Model Selection
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    William B. Poland, Ross D. Shachter
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    UAI
    1994
    91views Artificial Intelligence» more  UAI 1994»
    A Probabilistic Calculus of Actions
    14 years 1 months ago
    A Probabilistic Calculus of Actions
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    Wepresenta symbolicmachinerythatadmits bothprobabilisticand causalinformation abouta givendomainand producesprobabilisticstatementsabouttheeffectofactions andtheimpactof observati...
    Judea Pearl
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    UAI
    1993
    122views Artificial Intelligence» more  UAI 1993»
    Jeffrey's rule of conditioning generalized to belief functions
    14 years 1 months ago
    Jeffrey's rule of conditioning generalized to belief functions
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    : Jeffrey’s rule of conditioning has been proposed in order to revise a probability measure by another probability function. We generalize it within the framework of the models b...
    Philippe Smets
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    UAI
    1994
    118views Artificial Intelligence» more  UAI 1994»
    A Logic for Default Reasoning About Probabilities
    14 years 1 months ago
    A Logic for Default Reasoning About Probabilities
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    A logic is de ned that allows to express information about statistical probabilities and about degrees of belief in speci c propositions. By interpreting the twotypes of probabili...
    Manfred Jaeger
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    UAI
    1993
    101views Artificial Intelligence» more  UAI 1993»
    Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties
    14 years 1 months ago
    Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties
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    William B. Poland, Ross D. Shachter
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    UAI
    1994
    120views Artificial Intelligence» more  UAI 1994»
    A Decision-based View of Causality
    14 years 1 months ago
    A Decision-based View of Causality
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    Most traditional models of uncertainty have focused on the associational relationship among variables as captured by conditional dependence. In order to successfully manage intell...
    David Heckerman, Ross D. Shachter
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    UAI
    1994
    117views Artificial Intelligence» more  UAI 1994»
    A New Look at Causal Independence
    14 years 1 months ago
    A New Look at Causal Independence
    Download  research.microsoft.com
    Heckerman (1993) defined causal independence in terms of a set of temporal conditional independence statements. These statements formalized certain types of causal interaction whe...
    David Heckerman, John S. Breese
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    UAI
    1993
    112views Artificial Intelligence» more  UAI 1993»
    On reasoning in networks with qualitative uncertainty
    14 years 1 months ago
    On reasoning in networks with qualitative uncertainty
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    In this paper some initialwork towards a new approach to qualitative reasoning under uncertainty is presented. This method is not only applicable to qualitative probabilistic reas...
    Simon Parsons, E. H. Mamdani
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    UAI
    1993
    88views Artificial Intelligence» more  UAI 1993»
    Using Causal Information and Local Measures to Learn Bayesian Networks
    14 years 1 months ago
    Using Causal Information and Local Measures to Learn Bayesian Networks
    Download  www.cs.toronto.edu
    In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
    Wai Lam, Fahiem Bacchus
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