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Activity Number: 73
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #319452 View Presentation
Title: Using L_1 Data Depth Unsupervised Classifier for Detecting Communities in Networks
Author(s): Yahui Tian* and Yulia R. Gel
Companies: and The University of Texas at Dallas
Keywords: Network Community Detection ; L_1 data depth ; Unsupervised Method ; Sparse Networks ; Robustness ; Nonparametric

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

Authors who are presenting talks have a * after their name.

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