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: Machine Learning and Interpretation in Neuroimaging
    sub title: 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers
  name:
    name part: Rish, Irina.
    role:
      role term: editor.
  name:
    name part: Langs, Georg.
    role:
      role term: editor.
  name:
    name part: Wehbe, Leila.
    role:
      role term: editor.
  name:
    name part: Cecchi, Guillermo.
    role:
      role term: editor.
  name:
    name part: Chang, Kai-min Kevin.
    role:
      role term: editor.
  name:
    name part: Murphy, Brian.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 129 p. 30 illus. online resource.
  abstract: This book constitutes the revised selected papers from the 4th International Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2014, held in Montreal, QC, Canada, in December 2014 as a satellite event of the 11th annual conference on Neural Information Processing Systems, NIPS 2014. The 10 MLINI 2014 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: networks and decoding; speech; clinics and cognition; and causality and time-series. In addition, the book contains the 3 best papers presented at MLINI 2013.
  table of contents: Networks and Decoding -- Multi-Task Learning for Interpretation of Brain Decoding Models -- The New Graph Kernels on Connectivity Networks for Identification of MCI -- Mapping Tractography Across Subjects -- Speech -- Automated speech analysis for psychosis evaluation -- Combining different modalities in classifying phonological categories -- Clinics and cognition -- Label-alignment-based Multi-task Feature Selection for Multimodal Classification of Brain Disease -- Leveraging Clinical Data to Enhance Localization of Brain Atrophy -- Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization -- Causality and time-series -- Classification-based Causality Detection in Time Series -- Fast and Improved SLEX Analysis of High-dimensional Time Series -- Best paper awards: MLINI 2013 -- Predicting Short-Term Cognitive Change from Longitudinal Neuroimaging Analysis -- Hyperalignment of Multi-Subject fMRI Data by Synchronized Projections -- An oblique approach to prediction of conversion to Alzheimer's Disease with multikernel Gaussian Processes. .
  note: edited by Irina Rish, Georg Langs, Leila Wehbe, Guillermo Cecchi, Kai-min Kevin Chang, Brian Murphy.
  subject:
    topic: Computer science
  subject:
    topic: Mathematical statistics
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Pattern Recognition
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Probability and Statistics in Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  classification: Q337.5
  classification: TK7882.P3
  classification: 006.4
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 9444
  identifier: 9783319451749
  identifier: http://dx.doi.org/10.1007/978-3-319-45174-9
  record info:
    record creation date: 160912
    record change date: 20160912082211.0
    record identifier: 978-3-319-45174-9