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Volumn , Issue , 2011, Pages 84-91

A preliminary evaluation of machine learning in algorithm selection for search problems

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM SELECTION; EXISTING SYSTEMS; MACHINE LEARNING TECHNIQUES; REAL-WORLD; SEARCH PROBLEM; STATISTICAL RELATIONAL LEARNING;

EID: 84867881025     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (24)

References (23)
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    • (1996) ECAI , pp. 160-164
    • Borrett, J.E.1    Tsang, E.P.K.2    Walsh, N.R.3
  • 4
    • 85166375551 scopus 로고    scopus 로고
    • How to solve it automatically: Selection among problem-solving methods
    • Fink, E. 1998. How to solve it automatically: Selection among Problem-Solving methods. In ICAPS, 128-136.
    • (1998) ICAPS , pp. 128-136
    • Fink, E.1
  • 6
    • 84893407198 scopus 로고    scopus 로고
    • Introduction to statistical relational learning
    • MIT Press. Gomes, C. P., and Selman, B. 2001.
    • Getoor, L., and Taskar, B. 2007. Introduction to Statistical Relational Learning. MIT Press. Gomes, C. P., and Selman, B. 2001. Algorithm portfolios. Artif. Intell. 126(1-2):43-62.
    • (2007) Algorithm Portfolios. Artif. Intell , vol.126 , Issue.1-2 , pp. 43-62
    • Getoor, L.1    Taskar, B.2
  • 7
    • 85017348041 scopus 로고    scopus 로고
    • Learning techniques for automatic algorithm portfolio selection
    • Guerri, A., and Milano, M. 2004. Learning techniques for automatic algorithm portfolio selection. In ECAI, 475-479.
    • (2004) ECAI , pp. 475-479
    • Guerri, A.1    Milano, M.2
  • 10
    • 85164392958 scopus 로고
    • A study of Cross-Validation and bootstrap for accuracy estimation and model selection
    • Kohavi, R. 1995. A study of Cross-Validation and bootstrap for accuracy estimation and model selection. In IJCAI, 1137-1143.
    • (1995) IJCAI , pp. 1137-1143
    • Kohavi, R.1
  • 11
    • 78149262600 scopus 로고    scopus 로고
    • Ensemble classification for constraint solver configuration
    • Kotthoff, L.; Miguel, I.; and Nightingale, P. 2010. Ensemble classification for constraint solver configuration. In CP, 321-329.
    • (2010) CP , pp. 321-329
    • Kotthoff, L.1    Miguel, I.2    Nightingale, P.3
  • 12
    • 0010007403 scopus 로고    scopus 로고
    • Algorithm selection using reinforcement learning
    • Lagoudakis, M. G., and Littman, M. L. 2000. Algorithm selection using reinforcement learning. In ICML, 511-518.
    • (2000) ICML , pp. 511-518
    • Lagoudakis, M.G.1    Littman, M.L.2
  • 14
    • 0031641796 scopus 로고    scopus 로고
    • Branch and bound algorithm selection by performance prediction
    • Lobjois, L., and Lemaitre, M. 1998. Branch and bound algorithm selection by performance prediction. In AAAI, 353-358.
    • (1998) AAAI , pp. 353-358
    • Lobjois, L.1    Lemaitre, M.2
  • 16
    • 58549118916 scopus 로고    scopus 로고
    • A self-adaptive multiengine solver for quantified boolean formulas
    • Pulina, L., and Tacchella, A. 2009. A self-adaptive multiengine solver for quantified boolean formulas. Constraints 14(1):80-116.
    • (2009) Constraints , vol.14 , Issue.1 , pp. 80-116
    • Pulina, L.1    Tacchella, A.2
  • 17
    • 0003056605 scopus 로고
    • The algorithm selection problem
    • Rice, J. R. 1976. The algorithm selection problem. Advances in Computers 15:65-118.
    • (1976) Advances in Computers , vol.15 , pp. 65-118
    • Rice, J.R.1
  • 19
    • 49749086726 scopus 로고    scopus 로고
    • Cross-disciplinary perspectives on meta-learning for algorithm selection
    • Smith-Miles, K. A. 2009. Cross-disciplinary perspectives on meta-learning for algorithm selection. ACM Comput. Surv. 41:6:16:25.
    • (2009) ACM Comput. Surv. , vol.41 , Issue.6 , pp. 1625
    • Smith-Miles, K.A.1
  • 20
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    • New techniques for algorithm portfolio design
    • Streeter, M. J., and Smith, S. F. 2008. New techniques for algorithm portfolio design. In UAI, 519-527.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.