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Volumn 19, Issue , 2011, Pages 133-154

Minimax regret of finite partial-monitoring games in stochastic environments

Author keywords

Imperfect feedback; Online learning; Regret analysis

Indexed keywords

ARTIFICIAL INTELLIGENCE; SOFTWARE ENGINEERING;

EID: 84867849262     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (41)

References (19)
  • 14
    • 84898440265 scopus 로고    scopus 로고
    • Master's thesis, Department of Computing Science, University of Alberta
    • V. Mnih. Efficient stopping rules. Master's thesis, Department of Computing Science, University of Alberta, 2008.
    • (2008) Efficient Stopping Rules
    • Mnih, V.1
  • 15
    • 56449108844 scopus 로고    scopus 로고
    • Empirical Bernstein stopping
    • W. W. Cohen, A. McCallum, and S. T. Roweis, editors, ACM
    • V. Mnih, Cs. Szepesvári, and J.-Y. Audibert. Empirical Bernstein stopping. In W. W. Cohen, A. McCallum, and S. T. Roweis, editors, ICML 2008, pages 672-679. ACM, 2008.
    • (2008) ICML 2008 , pp. 672-679
    • Mnih, V.1    Szepesvári, Cs.2    Audibert, J.-Y.3
  • 16
    • 84898400841 scopus 로고    scopus 로고
    • Sequential learning for optimal monitoring of multi-channel wireless networks
    • A. Pallavi, R. Zheng, and Cs. Szepesvári. Sequential learning for optimal monitoring of multi-channel wireless networks. In INFOCOMM, 2011.
    • (2011) INFOCOMM
    • Pallavi, A.1    Zheng, R.2    Szepesvári, Cs.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.