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    UAI
    2001
    113views Artificial Intelligence» more  UAI 2001»
    Improved learning of Bayesian networks
    13 years 6 months ago
    Improved learning of Bayesian networks
    Download  functionalgenomics.upf.edu
    The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
    Tomás Kocka, Robert Castelo
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    IJCAI
    2003
    105views Artificial Intelligence» more  IJCAI 2003»
    Optimal Time-Space Tradeoff in Probabilistic Inference
    13 years 6 months ago
    Optimal Time-Space Tradeoff in Probabilistic Inference
    Download  dli.iiit.ac.in
    Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
    David Allen, Adnan Darwiche
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    IICAI
    2003
    137views Artificial Intelligence» more  IICAI 2003»
    Performance Analysis of an Acyclic Genetic approach to Learn Bayesian Network Structure
    13 years 6 months ago
    Performance Analysis of an Acyclic Genetic approach to Learn Bayesian Network Structure
    Download  digital.cs.usu.edu
    Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...
    Pankaj B. Gupta, Vicki H. Allan
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    FLAIRS
    2003
    84views Artificial Intelligence» more  FLAIRS 2003»
    Using Bayesian Networks for Cleansing Trauma Data
    13 years 6 months ago
    Using Bayesian Networks for Cleansing Trauma Data
    Download  www.aaai.org
    Medical data is unique due to its large volume, heterogeneity and complexity. This necessitates costly active participation of medical domain experts in the task of cleansing medi...
    Prashant Doshi, Lloyd Greenwald, John R. Clarke
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    FLAIRS
    2003
    133views Artificial Intelligence» more  FLAIRS 2003»
    An Extension of the Differential Approach for Bayesian Network Inference to Dynamic Bayesian Networks
    13 years 6 months ago
    An Extension of the Differential Approach for Bayesian Network Inference to Dynamic Bayesian Networks
    Download  dfki.de
    We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
    Boris Brandherm
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    EUSFLAT
    2003
    155views Fuzzy Logic» more  EUSFLAT 2003»
    Bayesian networks for transport decision scenarios
    13 years 6 months ago
    Bayesian networks for transport decision scenarios
    Download  www.eusflat.org
    Bayesian networks are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. We will analyze Bayesian network...
    Alexander Holland
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    EUSFLAT
    2003
    152views Fuzzy Logic» more  EUSFLAT 2003»
    Bayesian networks for continuous values and uncertainty in the learning process
    13 years 6 months ago
    Bayesian networks for continuous values and uncertainty in the learning process
    Download  www.eusflat.org
    This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The dat...
    J. F. Baldwin, E. Di Tomaso
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    FLAIRS
    2006
    80views Artificial Intelligence» more  FLAIRS 2006»
    Generating Realistic Large Bayesian Networks by Tiling
    13 years 6 months ago
    Generating Realistic Large Bayesian Networks by Tiling
    Download  www.aaai.org
    In this paper we present an algorithm and software for generating arbitrarily large Bayesian Networks by tiling smaller real-world known networks. The algorithm preserves the stru...
    Ioannis Tsamardinos, Alexander R. Statnikov, Laura...
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    FLAIRS
    2004
    115views Artificial Intelligence» more  FLAIRS 2004»
    An Empirical Study of Probability Elicitation Under Noisy-OR Assumption
    13 years 6 months ago
    An Empirical Study of Probability Elicitation Under Noisy-OR Assumption
    Download  www.pitt.edu
    Bayesian network is a popular modeling tool for uncertain domains that provides a compact representation of a joint probability distribution among a set of variables. Even though ...
    Adam Zagorecki, Marek J. Druzdzel
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    BIOCOMP
    2006
    120views Bioinformatics» more  BIOCOMP 2006»
    Learning Genetic and Gene Bayesian Networks with Hidden Variables: Bilayer Verification Algorithm
    13 years 6 months ago
    Learning Genetic and Gene Bayesian Networks with Hidden Variables: Bilayer Verification Algorithm
    Download  ww1.ucmss.com
    To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
    Jason E. Aten
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