메뉴 건너뛰기




Volumn , Issue , 2015, Pages

Training convolutional networks with noisy labels

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONVOLUTION; LARGE DATASET;

EID: 85083950731     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (279)

References (37)
  • 7
    • 77955655063 scopus 로고    scopus 로고
    • Semi-supervised learning in gigantic image collections
    • Bengio, Y., Schuurmans, D., Lafferty, J.D., Williams, C.K.I., and Culotta, A. eds
    • Fergus, Rob, Weiss, Yair, and Torralba, Antonio. Semi-supervised learning in gigantic image collections. In Bengio, Y., Schuurmans, D., Lafferty, J.D., Williams, C.K.I., and Culotta, A. (eds.), Advances in Neural Information Processing Systems 22, pp. 522–530. 2009.
    • (2009) Advances in Neural Information Processing Systems , vol.22 , pp. 522-530
    • Fergus, R.1    Weiss, Y.2    Torralba, A.3
  • 10
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • Hinton, G. E. and Salakhutdinov, R. R. Reducing the dimensionality of data with neural networks. Science, 313(5786):504–507, 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 19
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Nov
    • Lecun, Y., Bottou, L., Bengio, Y., and Haffner, P. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324, Nov 1998.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • Lecun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 21
    • 70450174344 scopus 로고    scopus 로고
    • Understanding and evaluating blind deconvolution algorithms
    • Levin, A., Weiss, Y., Durand, F., and Freeman, W. T. Understanding and evaluating blind deconvolution algorithms. In CVPR, 2009.
    • (2009) CVPR
    • Levin, A.1    Weiss, Y.2    Durand, F.3    Freeman, W.T.4
  • 24
    • 84898030282 scopus 로고    scopus 로고
    • A study of the effect of different types of noise on the precision of supervised learning techniques
    • Nettleton, David, Orriols-Puig, Albert, and Fornells, Albert. A study of the effect of different types of noise on the precision of supervised learning techniques. Artificial Intelligence Review, 33(4):275–306, 2010.
    • (2010) Artificial Intelligence Review , vol.33 , Issue.4 , pp. 275-306
    • Nettleton, D.1    Orriols-Puig, A.2    Fornells, A.3
  • 31
    • 54749092170 scopus 로고    scopus 로고
    • 80 million tiny images: A large data set for nonparametric object and scene recognition. Pattern analysis and machine intelligence
    • Nov
    • Torralba, A., Fergus, R., and Freeman, W.T. 80 million tiny images: A large data set for nonparametric object and scene recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(11):1958–1970, Nov 2008.
    • (2008) IEEE Transactions on , vol.30 , Issue.11 , pp. 1958-1970
    • Torralba, A.1    Fergus, R.2    Freeman, W.T.3
  • 32
    • 0036678198 scopus 로고    scopus 로고
    • Randomized response, statistical disclosure control and misclassificatio: A review
    • van den Hout, Ardo and van der Heijden, Peter G.M. Randomized response, statistical disclosure control and misclassificatio: a review. International Statistical Review, 70(2):269–288, 2002.
    • (2002) International Statistical Review , vol.70 , Issue.2 , pp. 269-288
    • van den Hout, A.1    van der Heijden, P.G.M.2
  • 34
    • 31844438481 scopus 로고    scopus 로고
    • Harmonic mixtures: Combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
    • Zhu, X. and Lafferty, J. Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning. In ICML, 2005.
    • (2005) ICML
    • Zhu, X.1    Lafferty, J.2
  • 35
    • 1942484430 scopus 로고    scopus 로고
    • Semi-supervised learning using gaussian fields and harmonic functions
    • Zhu, X., Ghahramani, Z., and Laffery, J. Semi-supervised learning using gaussian fields and harmonic functions. In ICML, 2003.
    • (2003) ICML
    • Zhu, X.1    Ghahramani, Z.2    Laffery, J.3
  • 36
    • 33745456231 scopus 로고    scopus 로고
    • Semi-supervised learning literature survey
    • University of Wisconsin Madison
    • Zhu, Xiaojin. Semi-supervised learning literature survey. In Computer Sciences TR 1530, University of Wisconsin Madison, 2008.
    • (2008) Computer Sciences TR 1530
    • Zhu, X.1
  • 37
    • 19544372918 scopus 로고    scopus 로고
    • Class noise vs. Attribute noise: A quantitative study
    • Zhu, Xingquan and Wu, Xindong. Class noise vs. attribute noise: A quantitative study. Artificial Intelligence Review, 22(3):177–210, 2004.
    • (2004) Artificial Intelligence Review , vol.22 , Issue.3 , pp. 177-210
    • Zhu, X.1    Wu, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.