Facundo Mémoli, m e m o l i @ m a t h . o s u . e d u
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Samir Chowdhury, c h o w d h u r y . 5 7 @ o s u . e d u
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| CSE 5339 -- Spring 2016 |
Tuesdays 1.50 -- 3.40 pm
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UH 0038.
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The emerging field of analysis of network analysis is another manifestation of the increasing availability of interesting data. Network data arises from applications in phylogenetics, social science, defence, commerce, neuroscience, and biology, to name a few sources.
Networks are most often directed, in the sense that weights attached to edges do not satisfy any symmetry property, and this asymmetry often precludes the applicability of many standard methods for data analysis.
In this topics course we will go over recent literature about the subject and will:
- survey the state of the art regarding algorithms for extracting information from network datasets (such as clustering)
- survey different sources of interesting network data
Several possible research directions will be discussed.
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The course has minimal requisites: it is designed for students from Computer Science and Engineering, and Mathematics having knowledge of undergrad level math. Some knowledge of geometry will be useful, but not necessary. The course will provide the opportunity to explore different aspects of the material: interested students will have the opportunity of implementing some algorithms and/or exploring some research papers on different aspects of both the underlying mathematics and/or the algorithmic procedures.
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