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Volumn 6, Issue 5, 2013, Pages 337-348

Scaling factorization machines to relational data

Author keywords

[No Author keywords available]

Indexed keywords

FACTORIZATION; LARGE DATASET; LEARNING ALGORITHMS; LEARNING SYSTEMS; MARKOV CHAINS; PREDICTIVE ANALYTICS; SUPPORT VECTOR MACHINES; SUPPORT VECTOR REGRESSION;

EID: 84881117508     PISSN: None     EISSN: 21508097     Source Type: Journal    
DOI: 10.14778/2535573.2488340     Document Type: Article
Times cited : (103)

References (24)
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    • Advances in collaborative filtering
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    • Y. Koren and R. M. Bell. Advances in collaborative filtering. In F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, editors, Recommender Systems Handbook, pages 145-186. Springer, 2011.
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    • Koren, Y.1    Bell, R.M.2
  • 9
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    • Distribution-based aggregation for relational learning with identifier attributes
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    • C. Perlich and F. Provost. Distribution-based aggregation for relational learning with identifier attributes. Mach. Learn., 62(1-2):65-105, Feb. 2006.
    • (2006) Mach. Learn , vol.62 , Issue.1-2 , pp. 65-105
    • Perlich, C.1    Provost, F.2
  • 13
    • 84863614151 scopus 로고    scopus 로고
    • Factorization machines with libFM
    • May
    • S. Rendle. Factorization machines with libFM. ACM Trans. Intell. Syst. Technol., 3(3):57:1-57:22, May 2012.
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    • Rendle, S.1
  • 14
    • 84898043294 scopus 로고    scopus 로고
    • Social network and click-through prediction with factorization machines
    • S. Rendle. Social network and click-through prediction with factorization machines. In KDD-Cup Workshop, 2012.
    • (2012) In KDD-Cup Workshop
    • Rendle, S.1
  • 17
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    • Probabilistic matrix factorization
    • J. Platt, D. Koller, Y. Singer, and S. Roweis, editors, Cambridge, MA. MIT Press
    • R. Salakhutdinov and A. Mnih. Probabilistic matrix factorization. In J. Platt, D. Koller, Y. Singer, and S. Roweis, editors, Advances in Neural Information Processing Systems 20, pages 1257-1264, Cambridge, MA, 2008. MIT Press.
    • (2008) Advances in Neural Information Processing Systems 20 , pp. 1257-1264
    • Salakhutdinov, R.1    Mnih, A.2
  • 19
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    • Scalable collaborative filtering approaches for large recommender systems
    • June
    • G. Takács, I. Pilászy, B. Németh, and D. Tikk. Scalable collaborative filtering approaches for large recommender systems. J. Mach. Learn. Res., 10:623-656, June 2009.
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    • Takács, G.1    Pilászy, I.2    Németh, B.3    Tikk, D.4
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    • Stochastic relational models for large-scale dyadic data using MCMC
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    • S. Zhu, K. Yu, and Y. Gong. Stochastic relational models for large-scale dyadic data using MCMC. In D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, editors, Advances in Neural Information Processing Systems 21, pages 1993-2000, 2009.
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    • Zhu, S.1    Yu, K.2    Gong, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.