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Volumn , Issue , 2013, Pages 998-1004

Multi-label learning with PRO LOSS

Author keywords

[No Author keywords available]

Indexed keywords

ALTERNATING DIRECTION METHOD OF MULTIPLIERS; EVALUATION CRITERIA; ITS EFFICIENCIES; MULTI-LABEL LEARNING; MULTIPLE LABELS; UPPER APPROXIMATION;

EID: 84893377206     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (29)

References (31)
  • 1
    • 33645323768 scopus 로고    scopus 로고
    • Hierarchical multi-label prediction of gene function
    • Barutcuoglu, Z.; Schapire, R. E.; and Troyanskaya, O. G. 2006. Hierarchical multi-label prediction of gene function. Bioinformatics 22(7):830-836.
    • (2006) Bioinformatics , vol.22 , Issue.7 , pp. 830-836
    • Barutcuoglu, Z.1    Schapire, R.E.2    Troyanskaya, O.G.3
  • 3
    • 3042597440 scopus 로고    scopus 로고
    • Learning multi-label scene classification
    • Boutell, M. R.; Luo, J.; Shen, X.; and Brown, C. M. 2004. Learning multi-label scene classification. Pattern Recognition 37(9):1757-1771.
    • (2004) Pattern Recognition , vol.37 , Issue.9 , pp. 1757-1771
    • Boutell, M.R.1    Luo, J.2    Shen, X.3    Brown, C.M.4
  • 4
    • 80051762104 scopus 로고    scopus 로고
    • Distributed optimization and statistical learning via the alternating direction method of multipliers
    • Boyd, S.; Parikh, N.; Chu, E.; Peleato, B.; and Eckstein, J. 2011. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning 3(1):1-122.
    • (2011) Foundations and Trends in Machine Learning , vol.3 , Issue.1 , pp. 1-122
    • Boyd, S.1    Parikh, N.2    Chu, E.3    Peleato, B.4    Eckstein, J.5
  • 13
    • 84890217212 scopus 로고    scopus 로고
    • Label ranking algorithms: A survey
    • Johannes Fürnkranz, E. H., ed
    • Gärtner, T., and Vembu, S. 2010. Label ranking algorithms: A survey. In Johannes Fürnkranz, E. H., ed., Preference Learning. 45-64.
    • (2010) Preference Learning , pp. 45-64
    • Gärtner, T.1    Vembu, S.2
  • 15
    • 84861398963 scopus 로고    scopus 로고
    • On the o(1/n) convergence rate of the Douglas-Rachford alternating direction method
    • He, B., and Yuan, X. 2012. On the o(1/n) convergence rate of the douglas-rachford alternating direction method. SIAM Journal of Numerical Analysis 50(2):700-709.
    • (2012) SIAM Journal of Numerical Analysis , vol.50 , Issue.2 , pp. 700-709
    • He, B.1    Yuan, X.2
  • 19
    • 77951171251 scopus 로고    scopus 로고
    • Msra-mm 2.0: A large-scale web multimedia dataset
    • Li, H.; Wang, M.; and Hua, X.-S. 2009. Msra-mm 2.0: A large-scale web multimedia dataset. In ICDM Workshops, 164-169.
    • (2009) ICDM Workshops , pp. 164-169
    • Li, H.1    Wang, M.2    Hua, X.-S.3
  • 21
    • 0033905095 scopus 로고    scopus 로고
    • BoosTexter: A boosting-based system for text categorization
    • Schapire, R. E., and Singer, Y. 2000. BoosTexter: A boosting-based system for text categorization. Machine Learning 39(2-3):135-168.
    • (2000) Machine Learning , vol.39 , Issue.2-3 , pp. 135-168
    • Schapire, R.E.1    Singer, Y.2
  • 22
    • 33745800276 scopus 로고    scopus 로고
    • Efficient learning of label ranking by soft projections onto polyhedra
    • Shalev-Shwartz, S., and Singer, Y. 2006. Efficient learning of label ranking by soft projections onto polyhedra. Journal of Machine Learning Research 7:1567-1599.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1567-1599
    • Shalev-Shwartz, S.1    Singer, Y.2
  • 25
    • 27144441097 scopus 로고    scopus 로고
    • An evaluation of statistical approaches to text categorization
    • Yang, Y. 1999. An evaluation of statistical approaches to text categorization. Information Retrieval 1(1-2):69-90.
    • (1999) Information Retrieval , vol.1 , Issue.1-2 , pp. 69-90
    • Yang, Y.1
  • 27
    • 33748366796 scopus 로고    scopus 로고
    • Multilabel neural networks with applications to functional genomics and text categorization
    • Zhang, M.-L., and Zhou, Z.-H. 2006. Multilabel neural networks with applications to functional genomics and text categorization. IEEE Transactions on Knowledge and Data Engineering 18(10):1338-1351.
    • (2006) IEEE Transactions on Knowledge and Data Engineering , vol.18 , Issue.10 , pp. 1338-1351
    • Zhang, M.-L.1    Zhou, Z.-H.2
  • 28
    • 33947681316 scopus 로고    scopus 로고
    • ML-KNN: A lazy learning approach to multi-label learning
    • Zhang, M.-L., and Zhou, Z.-H. 2007a. ML-KNN: A lazy learning approach to multi-label learning. Pattern Recognition 40(7):2038-2048.
    • (2007) Pattern Recognition , vol.40 , Issue.7 , pp. 2038-2048
    • Zhang, M.-L.1    Zhou, Z.-H.2
  • 30
    • 67650995440 scopus 로고    scopus 로고
    • Feature selection for multi-label naive bayes classification
    • Zhang, M.; Peña, J.; and Robles, V. 2009. Feature selection for multi-label naive bayes classification. Information Science 179(19):3218-3229.
    • (2009) Information Science , vol.179 , Issue.19 , pp. 3218-3229
    • Zhang, M.1    Peña, J.2    Robles, V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.