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Volumn 07-12-June-2015, Issue , 2015, Pages 1483-1491

Semi-supervised low-rank mapping learning for multi-label classification

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; MAPPING; PATTERN RECOGNITION;

EID: 84959193236     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298755     Document Type: Conference Paper
Times cited : (84)

References (36)
  • 3
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning and Re-search, 7:2399-2434, 2006
    • (2006) Journal of Machine Learning and Re-search , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 4
    • 85162050606 scopus 로고    scopus 로고
    • Label embedding trees for large multi-class tasks
    • S. Bengio, J. Weston, and D. Grangier. Label embedding trees for large multi-class tasks. In Proc. of NIPS, pages 1-9, 2010
    • (2010) Proc. of NIPS , pp. 1-9
    • Bengio, S.1    Weston, J.2    Grangier, D.3
  • 7
    • 84863765409 scopus 로고    scopus 로고
    • A singular value thresholding algorithm for matrix completion
    • J. Cai, E. Candes, and Z. Shen. A singular value thresholding algorithm for matrix completion. SIAM J. Optimization, 2(2):569-592, 2009
    • (2009) SIAM J. Optimization , vol.2 , Issue.2 , pp. 569-592
    • Cai, J.1    Candes, E.2    Shen, Z.3
  • 8
    • 84877784525 scopus 로고    scopus 로고
    • Feature-aware label space dimension reduction for multi-label classification
    • Y. Chen and H. Lin. Feature-aware label space dimension reduction for multi-label classification. In Proc. of NIPS, 2012
    • (2012) Proc. of NIPS
    • Chen, Y.1    Lin, H.2
  • 9
    • 77956522919 scopus 로고    scopus 로고
    • Bayes optimal multilabel classification via probabilistic classifier chains
    • K. Dembczynski, W. Cheng, and E. Hullermeier. Bayes optimal multilabel classification via probabilistic classifier chains. In Proc. of ICML, pages 279-286, 2010
    • (2010) Proc. of ICML , pp. 279-286
    • Dembczynski, K.1    Cheng, W.2    Hullermeier, E.3
  • 10
    • 84865223006 scopus 로고    scopus 로고
    • On label dependence and loss minimization in multilabel classification
    • K. Dembczynski, W. Waegeman, W. Cheng, and E. Hullermeier. On label dependence and loss minimization in multilabel classification. Machine Learning, 88(1):5-45, 2012
    • (2012) Machine Learning , vol.88 , Issue.1 , pp. 5-45
    • Dembczynski, K.1    Waegeman, W.2    Cheng, W.3    Hullermeier, E.4
  • 11
    • 21244486307 scopus 로고    scopus 로고
    • Multicategory proximal support vector machine classifiers
    • G. Fung and O. Mangasarian. Multicategory proximal support vector machine classifiers. Machine Learning, 59(1):77-97, 2005
    • (2005) Machine Learning , vol.59 , Issue.1 , pp. 77-97
    • Fung, G.1    Mangasarian, O.2
  • 12
    • 33745767102 scopus 로고    scopus 로고
    • Collective multilabel classification
    • N. Ghamrawi and A. Mccallum. Collective multilabel classification. In Proc. of CIKM, pages 195-200, 2005
    • (2005) Proc. of CIKM , pp. 195-200
    • Ghamrawi, N.1    McCallum, A.2
  • 15
    • 85167466122 scopus 로고    scopus 로고
    • Multi-label learning by exploiting label correlations locally
    • S. Huang and Z. Zhou. Multi-label learning by exploiting label correlations locally. In Proc. of AAAI, 2012
    • (2012) Proc. of AAAI
    • Huang, S.1    Zhou, Z.2
  • 16
    • 84896062998 scopus 로고    scopus 로고
    • Active learning with multi-label SVM classification
    • X. Li and Y. Guo. Active learning with multi-label svm classification. In Proc. of IJCAI, 2013
    • (2013) Proc. of IJCAI
    • Li, X.1    Guo, Y.2
  • 18
    • 84919914091 scopus 로고    scopus 로고
    • Multi-label classification via feature-aware implicit label space encoding
    • Z. Lin, G. Ding, M. Hu, and J. Wang. Multi-label classification via feature-aware implicit label space encoding. In Proc. of ICML, 2014
    • (2014) Proc. of ICML
    • Lin, Z.1    Ding, G.2    Hu, M.3    Wang, J.4
  • 19
    • 85162350693 scopus 로고    scopus 로고
    • Linearized alternating direction method with adaptive penalty for low-rank representation
    • Z. Lin, R. Liu, and Z. Su. Linearized alternating direction method with adaptive penalty for low-rank representation. In Proc. of NIPS, pages 612-620, 2011
    • (2011) Proc. of NIPS , pp. 612-620
    • Lin, Z.1    Liu, R.2    Su, Z.3
  • 21
    • 80052722936 scopus 로고    scopus 로고
    • Inexact alternating direction methods for image recovery
    • M. Ng, F. Wang, and X. Yuan. Inexact alternating direction methods for image recovery. SIAM J. on Scientific Comput-ing, 34(3):1643-1668, 2011
    • (2011) SIAM J. on Scientific Comput-ing , vol.34 , Issue.3 , pp. 1643-1668
    • Ng, M.1    Wang, F.2    Yuan, X.3
  • 22
    • 84900870389 scopus 로고    scopus 로고
    • The sun attribute database: Beyond categories for deeper scene understanding
    • G. Patterson, C. Xu, H. Su, and J. Hays. The sun attribute database: Beyond categories for deeper scene understanding. International Journal of Computer Vision, 108:59-81, 2014
    • (2014) International Journal of Computer Vision , vol.108 , pp. 59-81
    • Patterson, G.1    Xu, C.2    Su, H.3    Hays, J.4
  • 23
    • 84880570485 scopus 로고    scopus 로고
    • A unified convergence analysis of block successive minimization methods for nonsmooth optimization
    • M. Razaviyayn, M. Hong, and Z. Luo. A unified convergence analysis of block successive minimization methods for nonsmooth optimization. SIAM J. on Optimization, 23(2):1126-1153, 2013
    • (2013) SIAM J. on Optimization , vol.23 , Issue.2 , pp. 1126-1153
    • Razaviyayn, M.1    Hong, M.2    Luo, Z.3
  • 24
    • 85026930159 scopus 로고    scopus 로고
    • Learning hierarchical multi-category text classifcation models
    • J. Rousu, C. Saunders, S. Szedmak, and J. Shawe-Taylor. Learning hierarchical multi-category text classifcation models. In Proc. of ICML, pages 774-751, 2005
    • (2005) Proc. of ICML , pp. 774-751
    • Rousu, J.1    Saunders, C.2    Szedmak, S.3    Shawe-Taylor, J.4
  • 25
    • 26944489846 scopus 로고    scopus 로고
    • Maximum-margin matrix factorization
    • N. Srebro, J. Rennie, and T. Jaakkola. Maximum-margin matrix factorization. In Proc. of NIPS, pages 1329-1336, 2004
    • (2004) Proc. of NIPS , pp. 1329-1336
    • Srebro, N.1    Rennie, J.2    Jaakkola, T.3
  • 26
    • 65449185036 scopus 로고    scopus 로고
    • Hypergraph spectral learning for multi-label classification
    • L. Sun, S. Ji, and J. Ye. Hypergraph spectral learning for multi-label classification. In Proc. of SIGKDD, pages 668-676, 2008
    • (2008) Proc. of SIGKDD , pp. 668-676
    • Sun, L.1    Ji, S.2    Ye, J.3
  • 27
    • 84959879004 scopus 로고    scopus 로고
    • Multi-label classification with principle label space transformation
    • F. Tai and H. Lin. Multi-label classification with principle label space transformation. In Proc. of ICML, 2010
    • (2010) Proc. of ICML
    • Tai, F.1    Lin, H.2
  • 30
    • 84908162712 scopus 로고    scopus 로고
    • Large-scale multi-label learning with missing labels
    • H. Yu, P. Jain, P. Kar, and I. Dhillon. Large-scale multi-label learning with missing labels. In Proc. of ICML, pages 17-26, 2014
    • (2014) Proc. of ICML , pp. 17-26
    • Yu, H.1    Jain, P.2    Kar, P.3    Dhillon, I.4
  • 31
    • 34249004618 scopus 로고    scopus 로고
    • Dimension reduction and coefficient estimation in multivariate linear regression
    • M. Yuan, A. Ekici, Z. Lu, and R. Monteiro. Dimension reduction and coefficient estimation in multivariate linear regression. J. R. Statist. Soc, 69(3):329-346, 2007
    • (2007) J. R. Statist Soc , vol.69 , Issue.3 , pp. 329-346
    • Yuan, M.1    Ekici, A.2    Lu, Z.3    Monteiro, R.4
  • 32
    • 33644783522 scopus 로고    scopus 로고
    • Self-tuning spectral clustering
    • L. Zelnik and P. Perona. Self-tuning spectral clustering. In Proc. of NIPS, pages 1601-1608, 2004
    • (2004) Proc. of NIPS , pp. 1601-1608
    • Zelnik, L.1    Perona, P.2
  • 34
    • 84862283912 scopus 로고    scopus 로고
    • Multi-label output codes using canonical correlation analysis
    • Y. Zhang and J. Schneider. Multi-label output codes using canonical correlation analysis. In Proc. of AISTATS, pages 873-882, 2011
    • (2011) Proc. of AISTATS , pp. 873-882
    • Zhang, Y.1    Schneider, J.2
  • 36
    • 70049095487 scopus 로고    scopus 로고
    • New multicategory boosting algorithms based on multicategory fisher consistent losses
    • H. Zou, J. Zhu, and T. Hastie. New multicategory boosting algorithms based on multicategory fisher consistent losses. Ann Appl. Stat, 2(4):1290-1306, 2008.
    • (2008) Ann Appl. Stat , vol.2 , Issue.4 , pp. 1290-1306
    • Zou, H.1    Zhu, J.2    Hastie, T.3


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