Activity Number:
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73
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistical Learning and Data Science
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Abstract #319452
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View Presentation
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Title:
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Using L_1 Data Depth Unsupervised Classifier for Detecting Communities in Networks
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Author(s):
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Yahui Tian* and Yulia R. Gel
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Companies:
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and The University of Texas at Dallas
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Keywords:
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Network Community Detection ;
L_1 data depth ;
Unsupervised Method ;
Sparse Networks ;
Robustness ;
Nonparametric
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Abstract:
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we propose a new algorithm for network community detection using L_1 depth in an unsupervised setting. We investigate applicability of relative L_1 depth to identify an unknown number of communities. We evaluate robustness of our approach in respect to varying network sparseness and illustrate the proposed methodology by case studies
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Authors who are presenting talks have a * after their name.