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Computational Modeling of Compositional and Relational Data Using Optimal Transport and Probabilistic Models
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Computational Modeling of Compositional and Relational Data Using Optimal Transport and Probabilistic Models. |
| 개인저자 | Ye, Jianbo. |
| 단체저자명 | The Pennsylvania State University. Information Sciences and Technology. |
| 발행사항 | [S.l.]: The Pennsylvania State University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 179 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12A(E). Dissertation Abstract International |
| ISBN | 9780438136175 |
| 학위논문주기 | Thesis (Ph.D.)--The Pennsylvania State University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A.
|
| 요약 | Quantitative researchers often view our world as a large collection of data generated and organized by the structures and functions of society and technology. Those data are usually presented and accessed with hierarchies, compositions, and rela |
| 요약 | The goal of this thesis research is to introduce new mathematical models and computational methods for analyzing large-scale compositional and relational data, as well as to validate the models' usefulness in solving real-world problems. We begi |
| 일반주제명 | Information science. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
