Denis Deratani Mauá
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    • On the complexity of propositional and relational credal networks
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    • Parameter Learning in ProbLog with Probabilistic Rules
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    • The Descriptive Complexity of Bayesian Network Specifications
    • The effect of combination functions on the complexity of relational Bayesian networks
    • University Entrance Exam as a Guiding Test for Artificial Intelligence
    • The Complexity of Bayesian Networks Specified by Propositional and Relational Languages
    • Better Initialization Heuristics for Order-based Bayesian Network Structure Learning
    • Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams
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    • Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution
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    • The Effect of Combination Functions on the Complexity of Relational Bayesian Networks
    • The structure and complexity of credal semantics
    • The Well-Founded Semantics of Cyclic Probabilistic Logic Programs
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    • Bayesian Networks of Bounded Treewith: A Performance Analysis
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    • On the Complexity of Propositional and Relational Credal Networks
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    • Probabilistic Inference in Credal Networks: New Complexity Results
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    • Trading off Speed and Accuracy in Multilabel Classification
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    • On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables
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Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams

Jan 1, 2016·
Denis Deratani Mauá
· 0 min read
URL DOI
Type
Journal article
Publication
International Journal of Approximate Reasoning
Last updated on Jan 1, 2016
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