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Volumn , Issue , 2011, Pages 145-152

Learning Mallows models with pairwise preferences

Author keywords

[No Author keywords available]

Indexed keywords

FUNDAMENTAL BUILDING BLOCKS; LEARNING PREFERENCES; LOG LIKELIHOOD; NON-PARAMETRIC ESTIMATIONS; ORDINAL RANKING; PAIR-WISE COMPARISON; REAL-WORLD DATASETS; SOCIAL CHOICE;

EID: 80053450574     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (163)

References (18)
  • 4
    • 2442707368 scopus 로고    scopus 로고
    • The repeated insertion model for rankings: Missing link between two subset choice models
    • Doignon, J., Pekec, A., and Regenwetter, M. The repeated insertion model for rankings: Missing link between two subset choice models. Psychometrika, 69(1):33-54, 2004. (Pubitemid 39436522)
    • (2004) Psychometrika , vol.69 , Issue.1 , pp. 33-54
    • Doignon, J.-P.1    Pekec, A.2    Regenwetter, M.3
  • 8
    • 56349095472 scopus 로고    scopus 로고
    • Non-parametric modeling of partially ranked data
    • Lebanon, G. and Mao, Y. Non-parametric modeling of partially ranked data. J. Machine Learning Research, 9: 2401-2429, 2008.
    • (2008) J. Machine Learning Research , vol.9 , pp. 2401-2429
    • Lebanon, G.1    Mao, Y.2
  • 10
    • 84863532748 scopus 로고    scopus 로고
    • Robust Approximation and Incremental Elicitation in Voting Protocols
    • to appear
    • Lu, T. and Boutilier, C. Robust Approximation and Incremental Elicitation in Voting Protocols 22nd Intl. Joint Conf. on AI (IJCAI-11), to appear, 2011.
    • (2011) 22nd Intl. Joint Conf. on AI (IJCAI-11)
    • Lu, T.1    Boutilier, C.2
  • 12
    • 0000827480 scopus 로고
    • Non-null ranking models
    • Mallows, C. L. Non-null ranking models. Biometrika, 44: 114-130, 1957.
    • (1957) Biometrika , vol.44 , pp. 114-130
    • Mallows, C.L.1
  • 14
    • 80053157821 scopus 로고    scopus 로고
    • Dirichlet process mixtures of generalized mallows models
    • Meila, M. and Chen, H. Dirichlet process mixtures of generalized mallows models. 26th Conf. on Uncertainty in AI (UAI-10), pp. 358-367, 2010.
    • (2010) 26th Conf. on Uncertainty in AI (UAI-10) , pp. 358-367
    • Meila, M.1    Chen, H.2
  • 15
    • 0037469110 scopus 로고    scopus 로고
    • Mixtures of distance-based models for ranking data
    • DOI 10.1016/S0167-9473(02)00165-2, PII S0167947302001652
    • Murphy, T. B. and Martin, D. Mixtures of distance-based models for ranking data. Computational Statistics and Data Analysis, 41:645-655, 2003. (Pubitemid 36065401)
    • (2003) Computational Statistics and Data Analysis , vol.41 , Issue.3-4 , pp. 645-655
    • Murphy, T.B.1    Martin, D.2
  • 16
    • 0002788893 scopus 로고    scopus 로고
    • A view of the EM algorithm that justifies incremental, sparse, and other variants
    • Jordan, M. (ed.), MIT Press, Cambridge, MA
    • Neal, R. and Hinton, G. A view of the EM algorithm that justifies incremental, sparse, and other variants. In Jordan, M. (ed.), Learning in Graphical Models, pp.355-368. MIT Press, Cambridge, MA, 1999.
    • (1999) Learning in Graphical Models , pp. 355-368
    • Neal, R.1    Hinton, G.2
  • 17
    • 0016443515 scopus 로고
    • The analysis of permutations
    • Plackett, R. The analysis of permutations. Applied Statistics, 24:193-202, 1975.
    • (1975) Applied Statistics , vol.24 , pp. 193-202
    • Plackett, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.