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Volumn , Issue , 2012, Pages 750-758

SPF-GMKL: Generalized multiple kernel learning with a million kernels

Author keywords

multiple kernel learning; spectral projected gradient descent; support vector machines

Indexed keywords

DATA POINTS; DATA SETS; GENERAL-PURPOSE OPTIMIZER; GRADIENT DESCENT; GRADIENT DIRECTION; GRADIENT NOISE; MULTIPLE KERNEL LEARNING; NASCENT FIELD; OBJECTIVE FUNCTION VALUES; OPTIMIZATION ALGORITHMS; OPTIMIZERS; PARAMETERIZATIONS; PROJECTED GRADIENT; REAL-WORLD APPLICATION; SECOND ORDERS; STEP SIZE; STEP SIZE SELECTION; TRAINING DATA;

EID: 84866010566     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2339530.2339648     Document Type: Conference Paper
Times cited : (79)

References (34)
  • 2
    • 84858766876 scopus 로고    scopus 로고
    • Exploring large feature spaces with hierarchical multiple kernel learning
    • F. R. Bach. Exploring large feature spaces with hierarchical multiple kernel learning. In NIPS, pages 105-112, 2008.
    • (2008) NIPS , pp. 105-112
    • Bach, F.R.1
  • 3
    • 23244467688 scopus 로고    scopus 로고
    • Multiple kernel learning, conic duality, and the SMO algorithm
    • F. R. Bach, G. R. G. Lanckriet, and M. I. Jordan. Multiple kernel learning, conic duality, and the SMO algorithm. In ICML, pages 6-13, 2004.
    • (2004) ICML , pp. 6-13
    • Bach, F.R.1    Lanckriet, G.R.G.2    Jordan, M.I.3
  • 5
    • 0034345420 scopus 로고    scopus 로고
    • Nonmonotone spectral projected gradient methods on convex sets
    • E. G. Birgin, J. M. Martinez, and M. Raydan. Nonmonotone spectral projected gradient methods on convex sets. SIAM J. on Optimization, 10(4):1196-1211, 2000.
    • (2000) SIAM J. on Optimization , vol.10 , Issue.4 , pp. 1196-1211
    • Birgin, E.G.1    Martinez, J.M.2    Raydan, M.3
  • 6
    • 10044235999 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • available at
    • C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
    • (2001) Software
    • Chang, C.-C.1    Lin, C.-J.2
  • 9
    • 65449122452 scopus 로고    scopus 로고
    • Learning subspace kernels for classification
    • J. Chen, S. Ji, B. Ceran, Q. Li, M. Wu, and J. Ye. Learning subspace kernels for classification. In KDD, pages 106-114, 2008.
    • (2008) KDD , pp. 106-114
    • Chen, J.1    Ji, S.2    Ceran, B.3    Li, Q.4    Wu, M.5    Ye, J.6
  • 11
    • 84858743760 scopus 로고    scopus 로고
    • Learning non-linear combinations of kernels
    • C. Cortes, M. Mohri, and A. Rostamizadeh. Learning non-linear combinations of kernels. In NIPS, pages 396-404, 2009.
    • (2009) NIPS , pp. 396-404
    • Cortes, C.1    Mohri, M.2    Rostamizadeh, A.3
  • 14
    • 85161982879 scopus 로고    scopus 로고
    • Learning kernels with radiuses of minimum enclosing balls
    • K. Gai, G. Chen, and C. Zhang. Learning kernels with radiuses of minimum enclosing balls. In NIPS, pages 649-657, 2010.
    • (2010) NIPS , pp. 649-657
    • Gai, K.1    Chen, G.2    Zhang, C.3
  • 15
    • 56449124689 scopus 로고    scopus 로고
    • Localized multiple kernel learning
    • M. Gonen and E. Alpaydin. Localized multiple kernel learning. In ICML, pages 352-359, 2008.
    • (2008) ICML , pp. 352-359
    • Gonen, M.1    Alpaydin, E.2
  • 20
    • 21844468979 scopus 로고    scopus 로고
    • Learning the kernel with hyperkernels
    • C. S. Ong, A. J. Smola, and R. C. Williamson. Learning the kernel with hyperkernels. JMLR, 6:1043-1071, 2005.
    • (2005) JMLR , vol.6 , pp. 1043-1071
    • Ong, C.S.1    Smola, A.J.2    Williamson, R.C.3
  • 21
    • 80053459750 scopus 로고    scopus 로고
    • Ultra-fast optimization algorithm for sparse multi kernel learning
    • June
    • F. Orabona and L. Jie. Ultra-fast optimization algorithm for sparse multi kernel learning. In ICML, pages 249-256, June 2011.
    • (2011) ICML , pp. 249-256
    • Orabona, F.1    Jie, L.2
  • 22
    • 77955993905 scopus 로고    scopus 로고
    • Online-batch strongly convex multi kernel learning
    • San Francisco, California, June
    • F. Orabona, L. Jie, and B. Caputo. Online-batch strongly convex multi kernel learning. In CVPR, pages 787-794, San Francisco, California, June 2010.
    • (2010) CVPR , pp. 787-794
    • Orabona, F.1    Jie, L.2    Caputo, B.3
  • 24
    • 0031542191 scopus 로고    scopus 로고
    • The barzilai and borwein gradient method for the large scale unconstrained minimization problem
    • M. Raydan. The barzilai and borwein gradient method for the large scale unconstrained minimization problem. SIAM J. on Optimization, 7(1):26-33, 1997.
    • (1997) SIAM J. on Optimization , vol.7 , Issue.1 , pp. 26-33
    • Raydan, M.1
  • 25
    • 85162475298 scopus 로고    scopus 로고
    • Non-parametric group orthogonal matching pursuit for sparse learning with multiple kernels
    • V. Sindhwani and A. C. Lozano. Non-parametric group orthogonal matching pursuit for sparse learning with multiple kernels. In NIPS, pages 2519-2527, 2011.
    • (2011) NIPS , pp. 2519-2527
    • Sindhwani, V.1    Lozano, A.C.2
  • 27
    • 33144470194 scopus 로고    scopus 로고
    • Efficient hyperkernel learning using second-order cone programming
    • I. W. Tsang and J. T. Kwok. Efficient hyperkernel learning using second-order cone programming. IEEE Transactions on Neural Networks, 17(1):48-58, 2006.
    • (2006) IEEE Transactions on Neural Networks , vol.17 , Issue.1 , pp. 48-58
    • Tsang, I.W.1    Kwok, J.T.2
  • 28
    • 71149100224 scopus 로고    scopus 로고
    • More generality in efficient multiple kernel learning
    • M. Varma and B. R. Babu. More generality in efficient multiple kernel learning. In ICML, page 134, 2009.
    • (2009) ICML , pp. 134
    • Varma, M.1    Babu, B.R.2
  • 29
    • 50649115912 scopus 로고    scopus 로고
    • Learning the discriminative power-invariance trade-off
    • M. Varma and D. Ray. Learning the discriminative power-invariance trade-off. In ICCV, pages 1-8, 2007.
    • (2007) ICCV , pp. 1-8
    • Varma, M.1    Ray, D.2
  • 30
    • 77953196456 scopus 로고    scopus 로고
    • Multiple kernels for object detection
    • A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman. Multiple kernels for object detection. In ICCV, pages 606-613, 2009.
    • (2009) ICCV , pp. 606-613
    • Vedaldi, A.1    Gulshan, V.2    Varma, M.3    Zisserman, A.4
  • 32
    • 44649123652 scopus 로고    scopus 로고
    • Multi-class discriminant kernel learning via convex programming
    • J. Ye, , S. Ji, and J. Chen. Multi-class discriminant kernel learning via convex programming. JMLR, 9:719-758, 2008.
    • (2008) JMLR , vol.9 , pp. 719-758
    • Ye, J.1    Ji, S.2    Chen, J.3
  • 33
    • 9944262108 scopus 로고    scopus 로고
    • A nonmonotone line search technique and its application to unconstrained optimization
    • H. Zhang and W. W. Hager. A nonmonotone line search technique and its application to unconstrained optimization. SIAM J. on Optimization, 14(4):1043-1056, 2004.
    • (2004) SIAM J. on Optimization , vol.14 , Issue.4 , pp. 1043-1056
    • Zhang, H.1    Hager, W.W.2
  • 34
    • 34547992388 scopus 로고    scopus 로고
    • Multiclass multiple kernel learning
    • A. Zien and C. S. Ong. Multiclass multiple kernel learning. In ICML, pages 1191-1198, 2007.
    • (2007) ICML , pp. 1191-1198
    • Zien, A.1    Ong, C.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.