Sparsity-encouraging Data-driven Priors in High-dimensional Problems.
dc.contributor.advisor | Ryan Martin, Chair | |
dc.contributor.advisor | Ana-Maria Staicu, Member | |
dc.contributor.advisor | Sujit Ghosh, Member | |
dc.contributor.advisor | Jonathan Williams, Member | |
dc.contributor.advisor | Amanda Lietz, Graduate School Representative | |
dc.contributor.author | Tang, Yiqi | |
dc.date.accepted | 2023-09-25 | |
dc.date.accessioned | 2023-10-31T12:30:25Z | |
dc.date.available | 2023-10-31T12:30:25Z | |
dc.date.defense | 2023-07-18 | |
dc.date.issued | 2023-07-18 | |
dc.date.released | 2023-10-31 | |
dc.date.reviewed | 2023-08-03 | |
dc.date.submitted | 2023-07-31 | |
dc.degree.discipline | Statistics | |
dc.degree.level | dissertation | |
dc.degree.name | Doctor of Philosophy | |
dc.identifier.other | deg34843 | |
dc.identifier.uri | https://www.lib.ncsu.edu/resolver/1840.20/41355 | |
dc.title | Sparsity-encouraging Data-driven Priors in High-dimensional Problems. |
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