rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advances in Probabilistic Graphical Models
  name:
    name part: Lucas, Peter.
    role:
      role term: editor.
  name:
    name part: Gámez, José A.
    role:
      role term: editor.
  name:
    name part: Salmerón, Antonio.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 386 p. online resource.
  abstract: In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence; contributions to the area are coming from computer science, mathematics, statistics and engineering. This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
  table of contents: Foundations -- Markov Equivalence in Bayesian Networks -- A Causal Algebra for Dynamic Flow Networks -- Graphical and Algebraic Representatives of Conditional Independence Models -- Bayesian Network Models with Discrete and Continuous Variables -- Sensitivity Analysis of Probabilistic Networks -- Inference -- A Review on Distinct Methods and Approaches to Perform Triangulation for Bayesian Networks -- Decisiveness in Loopy Propagation -- Lazy Inference in Multiply Sectioned Bayesian Networks Using Linked Junction Forests -- Learning -- A Study on the Evolution of Bayesian Network Graph Structures -- Learning Bayesian Networks with an Approximated MDL Score -- Learning of Latent Class Models by Splitting and Merging Components -- Decision Processes -- An Efficient Exhaustive Anytime Sampling Algorithm for Influence Diagrams -- Multi-currency Influence Diagrams -- Parallel Markov Decision Processes -- Applications -- Applications of HUGIN to Diagnosis and Control of Autonomous Vehicles -- Biomedical Applications of Bayesian Networks -- Learning and Validating Bayesian Network Models of Gene Networks -- The Role of Background Knowledge in Bayesian Classification.
  note: edited by Peter Lucas, José A. Gámez, Antonio Salmerón.
  subject:
    topic: Mathematics
  subject:
    topic: Artificial intelligence
  subject:
    topic: Mathematical models
  subject:
    topic: Probabilities
  subject:
    topic: Discrete mathematics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Discrete Mathematics
  subject:
    topic: Mathematical Modeling and Industrial Mathematics
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 214
  identifier: 9783540689966
  identifier: http://dx.doi.org/10.1007/978-3-540-68996-6
  record info:
    record creation date: 100301
    record change date: 20151204190724.0
    record identifier: 978-3-540-68996-6