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Abstract Details
Activity Number:
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33
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract - #306007 |
Title:
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Multi-Scale Geometry and Motif Matching in Relational Data Learning
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Author(s):
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Hui Wang*+
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Companies:
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University of California at Davis
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Address:
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5000 Orchard Park Circle, Davis, CA, 95616, United States
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Keywords:
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Data Cloud Geometry ;
functional MRI data ;
Motif Matching ;
Classification ;
Clustering ;
Learning
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Abstract:
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We propose multi-scale geometry and motif matching, a method to implement classification for relational data. By utilizing data cloud geometry, we obtain a scale-sensitive hierarchical geometry, then by matching the geometry, we calculate the distance between subjects, and use it as a metric for classification. Multi-scale geometry and motif matching is illustrated for the analysis of functional MRI correlation data in diagnosis for autism spectrum disorder (ASD).
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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