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Volumn , Issue , 2010, Pages

Multitask learning without label correspondences

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

EID: 85162067125     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (37)

References (21)
  • 1
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning
    • R. Caruana. Multitask learning. Machine Learning, 28:41-75, 1997.
    • (1997) Machine Learning , vol.28 , pp. 41-75
    • Caruana, R.1
  • 2
    • 55149088329 scopus 로고    scopus 로고
    • Convex multi-task feature learning
    • Andreas Argyriou, Theodoros Evgeniou, and Massimiliano Pontil. Convex multi-task feature learning. Mach. Learn., 73(3):243-272, 2008.
    • (2008) Mach. Learn. , vol.73 , Issue.3 , pp. 243-272
    • Argyriou, A.1    Evgeniou, T.2    Pontil, M.3
  • 4
    • 27844439373 scopus 로고    scopus 로고
    • A framework for learning predictive structures from multiple tasks and unlabeled data
    • Rie Kubota Ando and Tong Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6:1817-1853, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1817-1853
    • Ando, R.K.1    Zhang, T.2
  • 5
    • 33746060884 scopus 로고    scopus 로고
    • Unifying divergence minimization and statistical inference via convex duality
    • H.U. Simon and G. Lugosi, editors, LNCS. Springer
    • Y. Altun and A.J. Smola. Unifying divergence minimization and statistical inference via convex duality. In H.U. Simon and G. Lugosi, editors, Proc. Annual Conf. Computational Learning Theory, LNCS, pages 139-153. Springer, 2006.
    • (2006) Proc. Annual Conf. Computational Learning Theory , pp. 139-153
    • Altun, Y.1    Smola, A.J.2
  • 6
    • 0032081028 scopus 로고
    • A D.C. optimization algorithm for solving the trust-region subproblem
    • T. Pham Dinh and L. Hoai An. A D.C. optimization algorithm for solving the trust-region subproblem. SIAM Journal on Optimization, 8(2):476-505, 1988.
    • (1988) SIAM Journal on Optimization , vol.8 , Issue.2 , pp. 476-505
    • Dinh, T.P.1    An, L.H.2
  • 9
    • 21844456299 scopus 로고    scopus 로고
    • Learning multiple tasks with kernel methods
    • Theodoros Evgeniou, Charles A. Micchelli, and Massimiliano Pontil. Learning multiple tasks with kernel methods. J. Mach. Learn. Res., 6:615-637, 2005.
    • (2005) J. Mach. Learn. Res. , vol.6 , pp. 615-637
    • Evgeniou, T.1    Micchelli, C.A.2    Pontil, M.3
  • 10
    • 50949125766 scopus 로고    scopus 로고
    • Learning from multiple sources
    • MIT Press
    • K. Crammer, M. Kearns, and J. Wortman. Learning from multiple sources. In NIPS 19, pages 321-328. MIT Press, 2007.
    • (2007) NIPS , vol.19 , pp. 321-328
    • Crammer, K.1    Kearns, M.2    Wortman, J.3
  • 12
    • 33746044362 scopus 로고    scopus 로고
    • Maximum entropy distribution estimation with generalized regularization
    • Gábor Lugosi and Hans U. Simon, editors Verlag, June. Springer
    • M. Dudík and R. E. Schapire. Maximum entropy distribution estimation with generalized regularization. In Gábor Lugosi and Hans U. Simon, editors, Proc. Annual Conf. Computational Learning Theory. Springer Verlag, June 2006.
    • (2006) Proc. Annual Conf. Computational Learning Theory
    • Dudík, M.1    Schapire, R.E.2
  • 16
    • 78149477774 scopus 로고    scopus 로고
    • On the convergence of the concave-convex procedure
    • Y. Bengio D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta editors, MIT Press
    • Bharath Sriperumbudur and Gert Lanckriet. On the convergence of the concave-convex procedure. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 1759-1767. MIT Press, 2009.
    • (2009) Advances in Neural Information Processing Systems , vol.22 , pp. 1759-1767
    • Sriperumbudur, B.1    Lanckriet, G.2
  • 17
    • 0003893955 scopus 로고    scopus 로고
    • R. Oldenbourg Verlag, Munich
    • B. Schölkopf. Support Vector Learning. R. Oldenbourg Verlag, Munich, 1997. Download: http://www.kernel-machines.org.
    • (1997) Support Vector Learning
    • Schölkopf, B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.