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Volumn , Issue , 2010, Pages 711-718

Mixed membership matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FRAMEWORKS; COLLABORATIVE FILTERING; DATA ANALYSIS; DATA SETS; GIBBS SAMPLING; LATENT FACTOR; MATRIX FACTORIZATIONS; MEMBERSHIP MATRIX;

EID: 77956495768     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (43)

References (16)
  • 1
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    • Airoldi, E., Blei, D., Fienberg, S., and Xing, E. Mixed membership stochastic blockmodels. JMLR, 9:1981-2014, 2008.
    • (2008) JMLR , vol.9 , pp. 1981-2014
    • Airoldi, E.1    Blei, D.2    Fienberg, S.3    Xing, E.4
  • 2
    • 0141607824 scopus 로고    scopus 로고
    • Latent Dirichlet allocation
    • Blei, D. M., Ng, A. Y., and Jordan, M. I. Latent Dirichlet allocation. JMLR, 3:993-1022, 2003.
    • (2003) JMLR , vol.3 , pp. 993-1022
    • Blei, D.M.1    Ng, A.Y.2    Jordan, M.I.3
  • 3
    • 33749236093 scopus 로고    scopus 로고
    • Collaborative prediction using ensembles of maximum margin matrix factorizations
    • DeCoste, D. Collaborative prediction using ensembles of maximum margin matrix factorizations. In ICML, 2006.
    • (2006) ICML
    • DeCoste, D.1
  • 4
    • 0021518209 scopus 로고
    • Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
    • Geman, S. and Geman, D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Pattern Analysis and Machine Intelligence, 6:721-741, 1984.
    • (1984) IEEE Pattern Analysis and Machine Intelligence , vol.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 6
    • 65449121157 scopus 로고    scopus 로고
    • Factorization meets the neighborhood: A multifaceted collaborative filtering model
    • Koren, Y. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In KDD, 2008.
    • (2008) KDD
    • Koren, Y.1
  • 7
    • 71149119166 scopus 로고    scopus 로고
    • Non-linear matrix factorization with Gaussian processes
    • Lawrence, N.D. and Urtasun, R. Non-linear matrix factorization with Gaussian processes. In ICML, 2009.
    • (2009) ICML
    • Lawrence, N.D.1    Urtasun, R.2
  • 8
    • 70449504107 scopus 로고    scopus 로고
    • Modeling user rating profiles for collaborative filtering
    • Marlin, B. Modeling user rating profiles for collaborative filtering. In NIPS, 2003.
    • (2003) NIPS
    • Marlin, B.1
  • 10
    • 36849028128 scopus 로고    scopus 로고
    • Applying collaborative filtering techniques to movie search for better ranking and browsing
    • Park, S-T. and Pennock, D. M. Applying collaborative filtering techniques to movie search for better ranking and browsing. In KDD, 2007.
    • (2007) KDD
    • Park, S.-T.1    Pennock, D.M.2
  • 11
    • 80052403470 scopus 로고    scopus 로고
    • Multi-HDP: A non parametric Bayesian model for tensor factorization
    • Porteous, I., Bart, E., and Welling, M. Multi-HDP: A non parametric Bayesian model for tensor factorization. In AAAI; 2008.
    • (2008) AAAI
    • Porteous, I.1    Bart, E.2    Welling, M.3
  • 12
    • 31844451557 scopus 로고    scopus 로고
    • Fast maximum margin matrix factorization for collaborative prediction
    • Rennie, J. and Srebro, N. Fast maximum margin matrix factorization for collaborative prediction. In ICML, 2005.
    • (2005) ICML
    • Rennie, J.1    Srebro, N.2
  • 13
    • 48349135120 scopus 로고    scopus 로고
    • Probabilistic matrix factorization
    • Salakhutdinov, R. and Mnih, A. Probabilistic matrix factorization. In NIPS, 2007.
    • (2007) NIPS
    • Salakhutdinov, R.1    Mnih, A.2
  • 14
    • 56449131205 scopus 로고    scopus 로고
    • Bayesian probabilistic matrix factorization using Markov chain Monte Mario
    • Salakhutdinov, R. and Mnih, A. Bayesian probabilistic matrix factorization using Markov chain Monte Mario. In ICML, 2008.
    • (2008) ICML
    • Salakhutdinov, R.1    Mnih, A.2
  • 15
    • 64149121935 scopus 로고    scopus 로고
    • Scalable collaborative filtering approaches for large recommender systems
    • Takács, G., Pilászy, I., Németh, B., and Tikk, D. Scalable collaborative filtering approaches for large recommender systems. JMLR, 10:623-656, 2009.
    • (2009) JMLR , vol.10 , pp. 623-656
    • Takács, G.1    Pilászy, I.2    Németh, B.3    Tikk, D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.