Reduced Order Method (ROM) and Anderson Acceleration for Iterative Schemes on Least Square Problems and Optimization, with Applications to Neural Networks and Partial Differential Equations (PDEs).

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dc.contributor.advisorKazufumi Ito, Chair
dc.contributor.advisorZhilin Li, Member
dc.contributor.advisorHangjie Ji, Member
dc.contributor.advisorHien Tran, Member
dc.contributor.authorXue, Tiancheng
dc.date.accepted2025-07-17
dc.date.accessioned2025-07-23T12:30:48Z
dc.date.available2025-07-23T12:30:48Z
dc.date.defense2025-07-03
dc.date.issued2025-07-03
dc.date.released2025-07-23
dc.date.reviewed2025-07-16
dc.date.submitted2025-07-12
dc.degree.disciplineOperations Research
dc.degree.leveldissertation
dc.degree.nameDoctor of Philosophy
dc.identifier.otherdeg43161
dc.identifier.urihttps://www.lib.ncsu.edu/resolver/1840.20/45577
dc.titleReduced Order Method (ROM) and Anderson Acceleration for Iterative Schemes on Least Square Problems and Optimization, with Applications to Neural Networks and Partial Differential Equations (PDEs).

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