Models and Inference with Network Structure
dc.contributor.author | Oselio, Brandon | |
dc.date.accessioned | 2020-01-27T16:25:15Z | |
dc.date.available | NO_RESTRICTION | |
dc.date.available | 2020-01-27T16:25:15Z | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/153433 | |
dc.description.abstract | In this thesis, the focus is on data that has network structure and on problems that benefit from the application of network-based algorithms. We target four research problems of interest: scalable and realistic models for network valued data, graph-based estimation of information theoretic quantities, summarization of complex time-varying data using dynamic graphs, and finally community detection on large multi-layer networks. This work advances the state-of-the-art in several directions. First, it introduces a new framework for complex network interaction data using the concept of edge exchangability. Second, it obtains new tight bounds for the multi-class Bayes error rate based on a graph-based technique, specifically the minimal spanning tree. Third, it introduces a new estimation method for Henze-Penrose divergence, a quantity relevant for graph-based multi-class classification. Fourth, it introduces adaptive directed information for estimating directed interaction networks. Fifth, the thesis presents a comprehensive approach to multi-layer network community detection. Throughout, examples are provided using real datasets, such as the Enron email dataset, an arXiv dataset, and Twitter. | |
dc.language.iso | en_US | |
dc.subject | network data | |
dc.subject | exchangeability | |
dc.subject | dynamic networks | |
dc.subject | network inference | |
dc.subject | meta learning | |
dc.subject | Bayes error rate | |
dc.title | Models and Inference with Network Structure | |
dc.type | Thesis | |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Electrical Engineering: Systems | |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | |
dc.contributor.committeemember | Hero III, Alfred O | |
dc.contributor.committeemember | Romero, Daniel M | |
dc.contributor.committeemember | Dempsey, Walter | |
dc.contributor.committeemember | Subramanian, Vijay Gautam | |
dc.subject.hlbsecondlevel | Electrical Engineering | |
dc.subject.hlbtoplevel | Engineering | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/153433/1/boselio_1.pdf | |
dc.identifier.orcid | 0000-0001-5729-9929 | |
dc.identifier.name-orcid | Oselio, Brandon; 0000-0001-5729-9929 | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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