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: Innovations in Neural Information Paradigms and Applications
  name:
    name part: Bianchini, Monica.
    role:
      role term: editor.
  name:
    name part: Maggini, Marco.
    role:
      role term: editor.
  name:
    name part: Scarselli, Franco.
    role:
      role term: editor.
  name:
    name part: Jain, Lakhmi C.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 293 p. online resource.
  abstract: This research book presents some of the most recent advances in neural information processing models including both theoretical concepts and practical applications. The contributions include: Advances in neural information processing paradigms Self organising structures Unsupervised and supervised learning of graph domains Neural grammar networks Model complexity in neural network learning Regularization and suboptimal solutions in neural learning Neural networks for the classification of vectors, sequences and graphs Metric learning for prototype-based classification Ensembles of neural networks Fraud detection using machine learning Computational modelling of neural multimodal integration This book is directed to the researchers, graduate students, professors and practitioner interested in recent advances in neural information processing paradigms and applications.
  table of contents: Advances in Neural Information Processing Paradigms -- Self-Organizing Maps for Structured Domains: Theory, Models, and Learning of Kernels -- Unsupervised and Supervised Learning of Graph Domains -- Neural Grammar Networks -- Estimates of Model Complexity in Neural-Network Learning -- Regularization and Suboptimal Solutions in Learning from Data -- Probabilistic Interpretation of Neural Networks for the Classification of Vectors, Sequences and Graphs -- Metric Learning for Prototype-Based Classification -- Bayesian Linear Combination of Neural Networks -- Credit Card Transactions, Fraud Detection, and Machine Learning: Modelling Time with LSTM Recurrent Neural Networks -- Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept.
  note: edited by Monica Bianchini, Marco Maggini, Franco Scarselli, Lakhmi C. Jain.
  subject:
    topic: Computer science
  subject:
    topic: Neurosciences
  subject:
    topic: Artificial intelligence
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Neurosciences
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 247
  identifier: 9783642040030
  identifier: http://dx.doi.org/10.1007/978-3-642-04003-0
  record info:
    record creation date: 100301
    record change date: 20151204153900.0
    record identifier: 978-3-642-04003-0