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Label-Efficient Bayesian Assessment of Black-Box Classifiers
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Label-Efficient Bayesian Assessment of Black-Box Classifiers. |
| 개인저자 | Ji, Disi. |
| 단체저자명 | University of California, Irvine. Computer Science - Ph.D.. |
| 발행사항 | [S.l.]: University of California, Irvine., 2020. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2020. |
| 형태사항 | 140 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-02B. Dissertation Abstract International |
| ISBN | 9798534655759 |
| 학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2020. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Advisor: Smyth, Padhraic. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Computer science. Probability. Accuracy. Active learning. Datasets. Algorithms. Sensitivity analysis. Advisors. Estimates. Experiments. Calibration. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
