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Distributionally Robust Optimization and Its Applications in Mathematical Finance, Statistics, and Reinforcement Learning
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Distributionally Robust Optimization and Its Applications in Mathematical Finance, Statistics, and Reinforcement Learning. |
| 개인저자 | Zhou, Zhengqing. |
| 단체저자명 | Stanford University. |
| 발행사항 | [S.l.]: Stanford University., 2021. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2021. |
| 형태사항 | 138 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-03B. Dissertation Abstract International |
| ISBN | 9798544204220 |
| 학위논문주기 | Thesis (Ph.D.)--Stanford University, 2021. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Advisor: Blanchet, Jose H.; Glynn, Peter W.; Papanicolaou, George. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Sample size. Optimization. Decision making. Operations research. Probability. Linear programming. Algorithms. Mathematics. Approximation. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
