SCOPUS 정보 검색 플랫폼

Proceedings of the 29th International Conference on Machine Learning, ICML 2012

Volumn 1, Issue , 2012, Pages 655-662

PAC subset selection in stochastic multi-armed bandits

(4) Kalyanakrishnan, Shivaram a Tewari, Ambuj b Auer, Peter c Stone, Peter b

a Yahoo Labs Bangalore (India)

b University of Texas at Austin (United States)

c UNIVERSITY OF LEOBEN (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

FORMAL ANALYSIS; LOWER BOUNDS; MULTI ARMED BANDIT; REGRET MINIMIZATION; SAMPLE COMPLEXITY; SAMPLE COMPLEXITY BOUNDS; SAMPLING ALGORITHM; SUBSET SELECTION;

LEARNING SYSTEMS; STOCHASTIC SYSTEMS;

ALGORITHMS;

EID: 84867131498 PISSN: None EISSN: None Source Type: Conference Proceeding
DOI: None Document Type: Conference Paper

Times cited : (387)

References (8)

1
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- Best arm identification in multi-armed bandits
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- Audibert, Jean-Yves, Bubeck, Sébastien, and Munos, Rémi. Best arm identification in multi-armed bandits. In Proc. COLT 2010, pp. 41-53. Omnipress, 2010.
- (2010) Proc. COLT 2010 , pp. 41-53
- Audibert, J.-Y.¹ Bubeck, S.² Munos, R.³

2
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- Finite-time analysis of the multiarmed bandit problem
- Auer, Peter, Cesa-Bianchi, Nicolò, and Fischer, Paul. Finite-time analysis of the multiarmed 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

3
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- Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems
- Even-Dar, Eyal, Mannor, Shie, and Mansour, Yishay. Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems. JMLR, 7:1079-1105, 2006.
- (2006) JMLR , vol.7 , pp. 1079-1105
- Even-Dar, E.¹ Mannor, S.² Mansour, Y.³

4
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- PhD thesis, Department of Computer Science, The University of Texas at Austin, December
- Kalyanakrishnan, Shivaram. Learning Methods for Sequential Decision Making with Imperfect Representations. PhD thesis, Department of Computer Science, The University of Texas at Austin, December 2011.
- (2011) Learning Methods for Sequential Decision Making with Imperfect Representations
- Kalyanakrishnan, S.¹

5
- 77956526578
- Efficient selection of multiple bandit arms: Theory and practice
- Omnipress
- Kalyanakrishnan, Shivaram and Stone, Peter. Efficient selection of multiple bandit arms: Theory and practice. In Proc. ICML 2010, pp. 511-518. Omnipress, 2010.
- (2010) Proc. ICML 2010 , pp. 511-518
- Kalyanakrishnan, S.¹ Stone, P.²

6
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- The sample complexity of exploration in the multi-armed bandit problem
- Mannor, Shie and Tsitsiklis, John N. The sample complexity of exploration in the multi-armed bandit problem. JMLR, 5:623-648, 2004.
- (2004) JMLR , vol.5 , pp. 623-648
- Mannor, S.¹ Tsitsiklis, J.N.²

7
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- Empirical Bernstein stopping
- ACM
- Mnih, Volodymyr, Szepesvári, Csaba, and Audibert, Jean-Yves. Empirical Bernstein stopping. In Proc. ICML 2008, pp. 672-679. ACM, 2008.
- (2008) Proc. ICML 2008 , pp. 672-679
- Mnih, V.¹ Szepesvári, C.² Audibert, J.-Y.³

8
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- Sequential PAC learning
- ACM
- Schuurmans, Dale and Greiner, Russell. Sequential PAC learning. In Proc. COLT 1995, pp. 377-384. ACM, 1995.
- (1995) Proc. COLT 1995 , pp. 377-384
- Schuurmans, D.¹ Greiner, R.²

* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.