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Volumn 3, Issue , 2014, Pages 2512-2537

Combinatorial partial monitoring game with linear feedback and its applications

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; E-LEARNING; LEARNING ALGORITHMS; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE);

EID: 84919902752     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (17)

References (17)
  • 2
    • 84898079018 scopus 로고    scopus 로고
    • Minimax policies for adversarial and stochastic bandits
    • Audibert, Jean-Yves and Bubeck, Sebastien. Minimax policies for adversarial and stochastic bandits. In COLT, 2009.
    • (2009) COLT
    • Audibert, J.-Y.1    Bubeck, S.2
  • 3
    • 0036568025 scopus 로고    scopus 로고
    • Finite-time analysis of the multi armed bandit problem
    • Auer, Peter, Cesa-Bianchi, Nicolo, and Fischer, Paul. Finite-time analysis of the multi armed bandit problem. Machine learning, 47(2-3):235-256, 2002.
    • (2002) Machine Learning , vol.47 , Issue.2-3 , pp. 235-256
    • Auer, P.1    Cesa-Bianchi, N.2    Fischer, P.3
  • 4
    • 84919930512 scopus 로고    scopus 로고
    • An adaptive algorithm for finite stochastic partial monitoring (extended version)
    • June
    • Bartok, G., Zolghadr, N., and Szepesvari, Cs. An adaptive algorithm for finite stochastic partial monitoring (extended version). In ICML, pp. 1-20, June 2012.
    • (2012) ICML , pp. 1-20
    • Bartok, G.1    Zolghadr, N.2    Szepesvari, C.3
  • 6
    • 84874045238 scopus 로고    scopus 로고
    • Regret analysis of stochastic and non stochastic multi-armed bandit problems
    • Bubeck, Sebastien and Cesa-Bianchi, Nicolo. Regret analysis of stochastic and non stochastic multi-armed bandit problems. Foundations and Trends in Machine Learning, 5(1):1-122, 2012.
    • (2012) Foundations and Trends in Machine Learning , vol.5 , Issue.1 , pp. 1-122
    • Bubeck, S.1    Cesa-Bianchi, N.2
  • 11
    • 84867858040 scopus 로고    scopus 로고
    • Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations
    • October
    • Gai, Yi, Krishnamachari, Bhaskar, and Jain, Rahul. Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations. IEEE/ACM Trans. Netw., 20(5):1466- 1478, October 2012. ISSN 1063-6692.
    • (2012) IEEE/ACM Trans. Netw. , vol.20 , Issue.5 , pp. 1466-1478
    • Gai, Y.1    Krishnamachari, B.2    Jain, R.3
  • 13
    • 0002899547 scopus 로고
    • Asymptotically efficient adaptive allocation rules
    • Lai, Tze Leung and Robbins, Herbert. Asymptotically efficient adaptive allocation rules. Advances in applied mathematics, 6(1):4-22, 1985.
    • (1985) Advances in Applied Mathematics , vol.6 , Issue.1 , pp. 4-22
    • Lai, T.L.1    Robbins, H.2
  • 15
    • 84898041886 scopus 로고    scopus 로고
    • Discrete prediction games with arbitrary feedback and loss
    • Springer
    • Piccolboni, Antonio and Schindelhauer, Christian. Discrete prediction games with arbitrary feedback and loss. In Computational Learning Theory, pp. 208-223. Springer, 2001.
    • (2001) Computational Learning Theory , pp. 208-223
    • Piccolboni, A.1    Schindelhauer, C.2
  • 16
    • 84893549814 scopus 로고
    • Some aspects of the sequential design of experiments
    • Springer
    • Robbins, Herbert. Some aspects of the sequential design of experiments. In Herbert Robbins Selected Papers, pp. 169-177. Springer, 1985.
    • (1985) Herbert Robbins Selected Papers , pp. 169-177
    • Robbins, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.