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Machine Learning and Interpretation in Neuroimaging : 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers / edited by Irina Rish, Georg Langs, Leila Wehbe, Guillermo Cecchi, Kai-min Kevin Chang, Brian Murphy.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Rish, Irina., Editor.
Langs, Georg, Editor.
Wehbe, Leila., Editor.
Cecchi, Guillermo., Editor.
Chang, Kai-min Kevin., Editor.
Murphy, Brian, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 9444
Lecture Notes in Artificial Intelligence, 2945-9141 ; 9444
Language:
English
Subjects (All):
Pattern recognition systems.
Computer vision.
Artificial intelligence.
Application software.
Computer science-Mathematics.
Mathematical statistics.
Data mining.
Automated Pattern Recognition.
Computer Vision.
Artificial Intelligence.
Computer and Information Systems Applications.
Probability and Statistics in Computer Science.
Data Mining and Knowledge Discovery.
Local Subjects:
Automated Pattern Recognition.
Computer Vision.
Artificial Intelligence.
Computer and Information Systems Applications.
Probability and Statistics in Computer Science.
Data Mining and Knowledge Discovery.
Physical Description:
1 online resource (X, 129 pages) : 30 illustrations
Edition:
1st ed. 2016.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2016.
System Details:
text file PDF
Summary:
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.
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. .
Other Format:
Printed edition:
ISBN:
978-3-319-45174-9
9783319451749
Access Restriction:
Restricted for use by site license.

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