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Title: Synthesis, Analysis and Re-organization od Sequential Data
Committee:
Dr. Davenport, ZhaAdvisor
Dr. Romberg, Chair
Dr. Song
Abstract:
The objective of the proposed research is to model complicated sequential data from the viewpoints of manifold learning and point processes. The work consists of three parts: (i) manifold-based sequential data synthesis, (ii) point process-based sequential data analysis, and (iii) re-organization of sequential data combining the point process model and the manifold assumptions. Various methods based on manifold learning and point processes are applied to deal with practical challenges in diverse applications. Additionally, some novel applications — e.g., modeling of IPTV user behavior, predicting patient flow in hospitals, and generating trailers from movies automatically — are explored based on the proposed methods.
