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Volumn , Issue , 2013, Pages 4545-4551

Multi-armed recommendation bandits for selecting state machine policies for robotic systems

Author keywords

[No Author keywords available]

Indexed keywords

AMAZON.COM; DRIVING STATE; MULTI ARMED BANDIT; NETFLIX; RECOMMENDATION TECHNIQUES; ROBOTIC SYSTEMS; STATE MACHINE;

EID: 84887305101     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2013.6631223     Document Type: Conference Paper
Times cited : (23)

References (18)
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    • Scalable collaborative filtering with jointly derived neighborhood interpolation weights
    • Bell. R.M. Koren. Y.: Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In: ICDM. (2007)
    • (2007) ICDM.
    • Bell, M.R.1    Koren, Y.2
  • 6
    • 77955644905 scopus 로고    scopus 로고
    • Factor in the neighbors Scalable and accurate collaborative filtering
    • Koren. Y.: Factor in the neighbors: Scalable and accurate collaborative filtering. ACM Transactions Knowledge Discovery Data 4 (2010) 1:1-1:24
    • (2010) ACM Transactions Knowledge Discovery Data 4 , vol.1 , pp. 1-14
    • Koren, Y.1
  • 7
    • 66849131425 scopus 로고    scopus 로고
    • Multi-task reinforcement learning in partially observable stochastic environments
    • Li. H. Liao. X. Carin. L.: Multi-task reinforcement learning in partially observable stochastic environments. Journal of Machine Learning Research (2009)
    • (2009) Journal of Machine Learning Research
    • Li, H.1    Liao, X.2    Carin, L.3
  • 16
    • 0002899547 scopus 로고
    • Asymptotically efficient adaptive allocation rules
    • Lai. T. Robbins. H.: Asymptotically efficient adaptive allocation rules. Advances in applied mathematics 6 (1985) 4-22
    • (1985) Advances in Applied Mathematics , vol.6 , pp. 4-22
    • Lai, T.1    Robbins, H.2
  • 17
    • 0036568025 scopus 로고    scopus 로고
    • Finite-time analysis of the multiarmed bandit problem
    • Auer. P. Cesa-Bianchi. N. Fischer. P.: Finite-time analysis of the multiarmed bandit problem. Machine learning 47 (2002) 235-256
    • (2002) Machine Learnin , vol.47 , pp. 235-256
    • Auer, P.1    Cesa-Bianchi, N.2    Fischer, P.3
  • 18
    • 84867112205 scopus 로고    scopus 로고
    • Hierarchical exploration for accelerating contextual bandits
    • Yue. Y. Hong. S.A. Guestrin. C.: Hierarchical exploration for accelerating contextual bandits. In: ICML. (2012)
    • (2012) ICML.
    • Yue, Y.1    Hong, A.S.2    Guestrin, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.