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Volumn , Issue , 2008, Pages

Active collaborative prediction with maximum margin matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE SAMPLING; FACTOR MODEL; LINEAR DISCRIMINANTS; MATRIX FACTORIZATIONS; MAXIMUM MARGIN; ONLINE RECOMMENDER SYSTEMS; PREDICTION TECHNIQUES; QUALITY OF PREDICTIONS; SEMIDEFINITE PROGRAMS;

EID: 84864576122     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (13)
  • 5
    • 34748918427 scopus 로고    scopus 로고
    • A Bayesian approach toward active learning for collaborative filtering
    • Jin, R., and Si, L. 2004. A Bayesian approach toward active learning for collaborative filtering. In Proc. of UAI, 278-285.
    • (2004) Proc. of UAI , pp. 278-285
    • Jin, R.1    Si, L.2
  • 6
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • Lee, D. D., and Seung, H. S. 2000. Algorithms for Non-negative Matrix Factorization. In NIPS, 556-562.
    • (2000) NIPS , pp. 556-562
    • Lee, D.D.1    Seung, H.S.2
  • 10
    • 31844451557 scopus 로고    scopus 로고
    • Fast maximum margin matrix factorization for collaborative prediction
    • Rennie, J., and Srebro, N. 2005. Fast maximum margin matrix factorization for collaborative prediction. In Proc. of ICML 2005, 713-719.
    • (2005) Proc. of ICML 2005 , pp. 713-719
    • Rennie, J.1    Srebro, N.2
  • 13
    • 0003007938 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • Tong, S., and Koller, D. 2000. Support Vector Machine Active Learning with Applications to Text Classification. In Proc. of ICML 2000.
    • (2000) Proc. of ICML 2000
    • Tong, S.1    Koller, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.