LDR | | 01948nam u200433 4500 |
001 | | 000000418690 |
005 | | 20190215163053 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438371569 |
035 | |
▼a (MiAaPQ)AAI10845443 |
035 | |
▼a (MiAaPQ)uchicago:14524 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 310 |
100 | 1 |
▼a Ha, Wooseok.
▼0 (orcid)0000-0002-9069-854X. |
245 | 10 |
▼a High-Dimensional Estimation and Optimization With Multiple Structured Signals. |
260 | |
▼a [S.l.]:
▼b The University of Chicago.,
▼c 2018. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
300 | |
▼a 175 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. |
500 | |
▼a Adviser: Rina Foygel Barber. |
502 | 1 |
▼a Thesis (Ph.D.)--The University of Chicago, 2018. |
520 | |
▼a 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 |
520 | |
▼a 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 |
590 | |
▼a School code: 0330. |
650 | 4 |
▼a Statistics. |
650 | 4 |
▼a Medical imaging. |
650 | 4 |
▼a Computer science. |
690 | |
▼a 0463 |
690 | |
▼a 0574 |
690 | |
▼a 0984 |
710 | 20 |
▼a The University of Chicago.
▼b Statistics. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0330 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000061
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a ***1012033 |