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Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning
Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning
상세정보
- 자료유형
- 학위논문파일 국외
- ISBN
- 9798535511139
- DDC
- 621.3
- 저자명
- Xu, Kaidi.
- 서명/저자
- Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning
- 발행사항
- [Sl] : Northeastern University, 2021
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- 형태사항
- 116 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
- 주기사항
- Advisor: Lin, Xue.
- 학위논문주기
- Thesis (Ph.D.)--Northeastern University, 2021.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 일반주제명
- Computer engineering
- 일반주제명
- Computer science
- 일반주제명
- Information technology
- 일반주제명
- Artificial intelligence
- 일반주제명
- Sparsity
- 일반주제명
- Internships
- 일반주제명
- Deep learning
- 일반주제명
- Datasets
- 일반주제명
- Success
- 일반주제명
- Dissertations & theses
- 일반주제명
- Noise
- 일반주제명
- Advisors
- 일반주제명
- Defense
- 일반주제명
- Performance evaluation
- 일반주제명
- COVID-19
- 일반주제명
- Power
- 일반주제명
- Experiments
- 일반주제명
- Neural networks
- 일반주제명
- Medical research
- 일반주제명
- Classification
- 일반주제명
- Linear programming
- 일반주제명
- Methods
- 일반주제명
- Algorithms
- 일반주제명
- Ablation
- 키워드
- AI Security
- 키워드
- Deep Learning
- 기타저자
- Northeastern University Electrical and Computer Engineering
- 기본자료저록
- Dissertations Abstracts International. 83-02B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008220131s2021 us c eng d■020 ▼a9798535511139
■035 ▼a(MiAaPQ)AAI28646717
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a621.3
■1001 ▼aXu, Kaidi.
■24510▼aCan We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning
■260 ▼a[Sl]▼bNortheastern University▼c2021
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2021
■300 ▼a116 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 83-02, Section: B.
■500 ▼aAdvisor: Lin, Xue.
■5021 ▼aThesis (Ph.D.)--Northeastern University, 2021.
■506 ▼aThis item must not be sold to any third party vendors.
■590 ▼aSchool code: 0160.
■650 4▼aComputer engineering
■650 4▼aComputer science
■650 4▼aInformation technology
■650 4▼aArtificial intelligence
■650 4▼aSparsity
■650 4▼aInternships
■650 4▼aDeep learning
■650 4▼aDatasets
■650 4▼aSuccess
■650 4▼aDissertations & theses
■650 4▼aNoise
■650 4▼aAdvisors
■650 4▼aDefense
■650 4▼aPerformance evaluation
■650 4▼aCOVID-19
■650 4▼aPower
■650 4▼aExperiments
■650 4▼aNeural networks
■650 4▼aMedical research
■650 4▼aClassification
■650 4▼aLinear programming
■650 4▼aNatural language processing
■650 4▼aMethods
■650 4▼aAlgorithms
■650 4▼aAblation
■653 ▼aAdversarial Machine Learning
■653 ▼aAI Security
■653 ▼aDeep Learning
■653 ▼aTrustworthy Machine Learning
■690 ▼a0464
■690 ▼a0489
■690 ▼a0984
■690 ▼a0800
■71020▼aNortheastern University▼bElectrical and Computer Engineering.
■7730 ▼tDissertations Abstracts International▼g83-02B.
■773 ▼tDissertation Abstract International
■790 ▼a0160
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16053335▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202202▼f2022
