Efficient computation for the noisy MAX

DOI10.1002/int.10080zbMath1028.68164OpenAlexW1990859777MaRDI QIDQ4416283

Severino F. Galán, Francisco Javier Díez

Publication date: 31 July 2003

Published in: International Journal of Intelligent Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/int.10080

zbMATH Keywords

Díez's algorithm

Mathematics Subject Classification ID

Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (13)

Learning first-order probabilistic models with combining rules ⋮ Unnamed Item ⋮ Generalizations of the noisy-or model ⋮ Structural learning of mixed noisy-or Bayesian networks ⋮ Probabilistic inference with noisy-threshold models based on a CP tensor decomposition ⋮ A Bayesian network interpretation of the Cox's proportional hazard model ⋮ The Hidden Elegance of Causal Interaction Models ⋮ Marginalization without Summation Exploiting Determinism in Factor Algebra ⋮ Negative probabilities in probabilistic logic programs ⋮ Variable elimination for influence diagrams with super value nodes ⋮ The Independent Choice Logic and Beyond ⋮ Triangulation Heuristics for BN2O Networks ⋮ Unnamed Item

Cites Work

• Networks of probabilistic events in discrete time.
• Local expression languages for probabilistic dependence
• Binary join trees for computing marginals in the Shenoy-Shafer architecture
• Independence of causal influence and clique tree propagation
• Lazy propagation: A junction tree inference algorithm based on lazy evaluation
• A FACTORIZED REPRESENTATION OF INDEPENDENCE OF CAUSAL INFLUENCE AND LAZY PROPAGATION
• An algebra of bayesian belief universes for knowledge‐based systems
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• Unnamed Item
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