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Optimization, Minimax, and Variational Inequality Problems: Algorithms and Applications
Optimization, Minimax, and Variational Inequality Problems: Algorithms and Applications
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105138
- ISBN
- 9798293866397
- DDC
- 658
- 저자명
- Wang, Nuozhou.
- 서명/저자
- Optimization, Minimax, and Variational Inequality Problems: Algorithms and Applications
- 발행사항
- [Sl] : University of Minnesota, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 186 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-03, Section: B.
- 주기사항
- Advisor: Zhang, Shuzhong.
- 학위논문주기
- Thesis (Ph.D.)--University of Minnesota, 2025.
- 초록/해제
- 요약Optimization, minimax, and variational inequality problems, particularly those involving certain structures, such as finite-sum structures, are central to modern machine learning and computational biology research. This thesis investigates the algorithmic complexity of such problems, focusing on first-order and second-order methods across different settings. A major theme is the studies of upper and lower bounds on the iteration complexity in each setting and algorithm class, identifying optimal or near-optimal status of the algorithms in question.
- 일반주제명
- Industrial engineering
- 일반주제명
- Engineering
- 일반주제명
- Systems science
- 키워드
- Optimization
- 기타저자
- University of Minnesota Industrial and Systems Engineering
- 기본자료저록
- Dissertations Abstracts International. 87-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798293866397
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a658
■1001 ▼aWang, Nuozhou.
■24510▼aOptimization, Minimax, and Variational Inequality Problems: Algorithms and Applications
■260 ▼a[Sl]▼bUniversity of Minnesota▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a186 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-03, Section: B.
■500 ▼aAdvisor: Zhang, Shuzhong.
■5021 ▼aThesis (Ph.D.)--University of Minnesota, 2025.
■520 ▼aOptimization, minimax, and variational inequality problems, particularly those involving certain structures, such as finite-sum structures, are central to modern machine learning and computational biology research. This thesis investigates the algorithmic complexity of such problems, focusing on first-order and second-order methods across different settings. A major theme is the studies of upper and lower bounds on the iteration complexity in each setting and algorithm class, identifying optimal or near-optimal status of the algorithms in question.
■590 ▼aSchool code: 0130.
■650 4▼aIndustrial engineering
■650 4▼aEngineering
■650 4▼aSystems science
■653 ▼aMinimax optimization
■653 ▼aOptimization
■653 ▼aVariational inequality problems
■690 ▼a0796
■690 ▼a0537
■690 ▼a0546
■690 ▼a0790
■71020▼aUniversity of Minnesota▼bIndustrial and Systems Engineering.
■7730 ▼tDissertations Abstracts International▼g87-03B.
■790 ▼a0130
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17359564▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
