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Computational and Statistical Aspects of High-dimensional Structured Estimation
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Chen, Sheng. |
| 단체저자명 | University of Minnesota. Computer Science. |
| 서명/저자사항 | Computational and Statistical Aspects of High-dimensional Structured Estimation. |
| 발행사항 | [S.l.] : University of Minnesota., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 272 p. |
| 소장본 주기 | School code: 0130. |
| ISBN | 9780438169227 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Arindam Banerjee. |
| 요약 | Modern statistical learning often faces high-dimensional data, for which the number of features that should be considered is very large. In consideration of various constraints encountered in data collection, such as cost and time, however, the |
| 요약 | Over the last two decades, sparsity has been one of the most popular structures to exploit when we estimate a high-dimensional parameter, which assumes that the number of nonzero elements in parameter vector/matrix is much smaller than its ambie |
| 요약 | In this thesis, we aim to make progress towards a unified framework for the estimation with general structures, by studying the high-dimensional structured linear model and other semi-parametric and non-convex extensions. In particular, we intro |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-12B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998787 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00026137 | 004 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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