자료유형 | 학위논문 |
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서명/저자사항 | High-Dimensional Estimation and Optimization With Multiple Structured Signals. |
개인저자 | Ha, Wooseok. |
단체저자명 | The University of Chicago. Statistics. |
발행사항 | [S.l.]: The University of Chicago., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 175 p. |
기본자료 저록 | Dissertation Abstracts International 80-02B(E). Dissertation Abstract International |
ISBN | 9780438371569 |
학위논문주기 | Thesis (Ph.D.)--The University of Chicago, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B.
Adviser: Rina Foygel Barber. |
요약 | Statistical recovery in high-dimensional statistics and signal processing often requests a determination of multiple structured signals from massive data. And depending on its application, either one or both of the signals may be of primarily i |
요약 | Chapter 2 describes a low-rank + sparse decomposition problem under data compression and we study rigorous statistical performance guarantee that is achievable using a joint convex optimization based estimator. It is well known that the convex r |
일반주제명 | Statistics. Medical imaging. Computer science. |
언어 | 영어 |
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