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A Geometric Perspective on Some Topics in Statistical Learning
A Geometric Perspective on Some Topics in Statistical Learning
- 자료유형
- 학위논문
- Control Number
- 0014998401
- International Standard Book Number
- 9780438325142
- Dewey Decimal Classification Number
- 310
- Main Entry-Personal Name
- Wei, Yuting.
- Publication, Distribution, etc. (Imprint
- [Sl] : University of California, Berkeley, 2018
- Publication, Distribution, etc. (Imprint
- Ann Arbor : ProQuest Dissertations & Theses, 2018
- Physical Description
- 188 p
- General Note
- Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
- General Note
- Advisers: Martin J. Wainwright
- Dissertation Note
- Thesis (Ph.D.)--University of California, Berkeley, 2018.
- Summary, Etc.
- 요약Modern science and engineering often generate data sets with a large sample size and a comparably large dimension which puts classic asymptotic theory into question in many ways. Therefore, the main focus of this thesis is to develop a fundament
- Summary, Etc.
- 요약Our treatment of these different problems shares the common theme of emphasizing the underlying geometric structure. To be more specific, in our hypothesis testing problem, the null and alternative are specified by a pair of convex cones. This c
- Summary, Etc.
- 요약These results demonstrate that, on one hand, one can benefit from respecting and making use of the underlying structure (optimal early stopping rule for different RKHS)
- Summary, Etc.
- 요약To evaluate the behavior of any statistical procedure, we follow the classic minimax framework and also discuss about more refined notion of local minimaxity.
- Subject Added Entry-Topical Term
- Statistics
- Added Entry-Corporate Name
- University of California, Berkeley Statistics
- Host Item Entry
- Dissertation Abstracts International. 80-01B(E).
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:556682