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Efficient and Scalable Markov Chain Monte Carlo Methods and Its Biological Applications
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Efficient and Scalable Markov Chain Monte Carlo Methods and Its Biological Applications. |
| 개인저자 | Zhang, Yizhe. |
| 단체저자명 | Duke University. Computational Biology and Bioinformatics. |
| 발행사항 | [S.l.]: Duke University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 169 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-09B(E). Dissertation Abstract International |
| ISBN | 9780355872736 |
| 학위논문주기 | Thesis (Ph.D.)--Duke University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Adviser: Lawerence Carin. |
| 이용제한사항 | This item is not available from ProQuest Dissertations & Theses. |
| 요약 | Markov Chain Monte Carlo (MCMC) stands as a fundamental approach for probabilistic inference in many computational statistics problems. Its application to computational biology and bioinformatics has attracted much attention in recent decades. A |
| 요약 | This thesis first focus on the theoretical connection (chapter 3), the unification and generalization of slice sampling and HMC. Base on these theoretical analysis, I present a generalized HMC that demonstrate efficient exploration of target dis |
| 요약 | The second part of the thesis, presented in chapter 4, concerns some advances remedying the practical issues of the generalized sampler, and how to scale up with large datasets. Chapter 4 first develops a novel scalable approximate sampling appr |
| 요약 | The remaining part of this thesis, consisting chapter 5 and chapter 6, discuss advances of scalable Bayesian method for some generic and core Biomedical applications. Two Bayesian inferential tasks involving latent variable model are discussed. |
| 요약 | Finally, chapter 7 concludes the dissertation and discussion some potential future studies in both methodology and applications. |
| 일반주제명 | Statistics. Bioinformatics. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
