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Volumn 43, Issue 6, 2010, Pages 2330-2339

Learning state machine-based string edit kernels

Author keywords

Learned edit distance; Marginalized kernel; String kernel

Indexed keywords

CONDITIONAL DISTRIBUTION; CONDITIONAL PROBABILITIES; EDIT DISTANCE; FISHER KERNELS; GENERATIVE MODEL; HAND WRITTEN CHARACTER RECOGNITION; MARGINALIZED KERNEL; PROBABILISTIC AUTOMATA; RATIONAL KERNELS; STATE MACHINE; STATE OF THE ART; STRING KERNEL;

EID: 76849108469     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2009.12.008     Document Type: Article
Times cited : (3)

References (31)
  • 3
    • 1542714925 scopus 로고    scopus 로고
    • Mismatch string kernels for discriminative protein classification
    • Leslie C., Eskin E., Cohen A., Weston J., and Noble W.S. Mismatch string kernels for discriminative protein classification. Bioinformatics 20 4 (2004) 467-476
    • (2004) Bioinformatics , vol.20 , Issue.4 , pp. 467-476
    • Leslie, C.1    Eskin, E.2    Cohen, A.3    Weston, J.4    Noble, W.S.5
  • 5
    • 60549100596 scopus 로고    scopus 로고
    • Hiv-1 coreceptor usage prediction without multiple alignments: an application of string kernels
    • Boisvert S., Marchand M., Laviolette F., and Corbeil J. Hiv-1 coreceptor usage prediction without multiple alignments: an application of string kernels. Retrovirology 5 1 (2008) 110
    • (2008) Retrovirology , vol.5 , Issue.1 , pp. 110
    • Boisvert, S.1    Marchand, M.2    Laviolette, F.3    Corbeil, J.4
  • 6
    • 4444273377 scopus 로고    scopus 로고
    • Protein homology detection using string alignment kernels
    • Saigo H., Vert J.-P., Ueda N., and Akutsu T. Protein homology detection using string alignment kernels. Bioinformatics 20 11 (2004) 1682-1689
    • (2004) Bioinformatics , vol.20 , Issue.11 , pp. 1682-1689
    • Saigo, H.1    Vert, J.-P.2    Ueda, N.3    Akutsu, T.4
  • 7
    • 0015960104 scopus 로고
    • The string-to-string correction problem
    • Wagner R., and Fischer M. The string-to-string correction problem. Journal of the ACM (JACM) 21 (1974) 168-173
    • (1974) Journal of the ACM (JACM) , vol.21 , pp. 168-173
    • Wagner, R.1    Fischer, M.2
  • 8
    • 33745360257 scopus 로고    scopus 로고
    • Edit distance-based kernel functions for structural pattern classification
    • Neuhaus M., and Bunke H. Edit distance-based kernel functions for structural pattern classification. Pattern Recognition 39 10 (2006) 1852-1863
    • (2006) Pattern Recognition , vol.39 , Issue.10 , pp. 1852-1863
    • Neuhaus, M.1    Bunke, H.2
  • 14
    • 33744981648 scopus 로고    scopus 로고
    • Learning stochastic edit distance: application in handwritten character recognition
    • Oncina J., and Sebban M. Learning stochastic edit distance: application in handwritten character recognition. Journal of Pattern Recognition 39 9 (2006) 1575-1587
    • (2006) Journal of Pattern Recognition , vol.39 , Issue.9 , pp. 1575-1587
    • Oncina, J.1    Sebban, M.2
  • 15
    • 33750299552 scopus 로고    scopus 로고
    • A discriminative model of stochastic edit distance in the form of a conditional transducer
    • 8th International Colloquium on Grammatical Inference ICGI'06, Springer, Berlin
    • M. Bernard, J.-C. Janodet, M. Sebban, A discriminative model of stochastic edit distance in the form of a conditional transducer, in: 8th International Colloquium on Grammatical Inference (ICGI'06), Lecture Notes in Computer Science, vol. 4201, Springer, Berlin, 2006, pp. 240-252.
    • (2006) Lecture Notes in Computer Science , vol.4201 , pp. 240-252
    • Bernard, M.1    Janodet, J.-C.2    Sebban, M.3
  • 16
    • 1642338802 scopus 로고    scopus 로고
    • Marginalized kernels for biological sequences
    • Tsuda K., Kin T., and Asai K. Marginalized kernels for biological sequences. Bioinformatics 18 90001 (2002) 268-275
    • (2002) Bioinformatics , vol.18 , Issue.90001 , pp. 268-275
    • Tsuda, K.1    Kin, T.2    Asai, K.3
  • 17
    • 0004019973 scopus 로고    scopus 로고
    • Convolution kernels on discrete structures
    • Technical Report, University of California, Santa Cruz
    • D. Haussler, Convolution kernels on discrete structures, Technical Report, University of California, Santa Cruz, 1999
    • (1999)
    • Haussler, D.1
  • 18
    • 76849102312 scopus 로고    scopus 로고
    • M.O. Dayhoff, R.M. Schwartz, B.C. Orcutt, A model of evolutionary change in proteins, in: M.O. Dayhoff, Atlas of Protein Sequence and Structure, 5, National Biomedical Research Foundation, Washington, DC, 1978, pp. 345-358.
    • M.O. Dayhoff, R.M. Schwartz, B.C. Orcutt, A model of evolutionary change in proteins, in: M.O. Dayhoff, Atlas of Protein Sequence and Structure, vol. 5, National Biomedical Research Foundation, Washington, DC, 1978, pp. 345-358.
  • 19
    • 0026458378 scopus 로고
    • Amino acid substitution matrices from protein blocks
    • Henikoff S., and Henikoff J.G. Amino acid substitution matrices from protein blocks. National Academy of Sciences of USA 89 22 (1992) 10915-10919
    • (1992) National Academy of Sciences of USA , vol.89 , Issue.22 , pp. 10915-10919
    • Henikoff, S.1    Henikoff, J.G.2
  • 21
    • 33746329568 scopus 로고    scopus 로고
    • Optimizing amino acid substitution matrices with a local alignment kernel
    • Hiroto S., Jean-Philippe V., and Tatsuya A. Optimizing amino acid substitution matrices with a local alignment kernel. BMC Bioinformatics 7 (2006) 246
    • (2006) BMC Bioinformatics , vol.7 , pp. 246
    • Hiroto, S.1    Jean-Philippe, V.2    Tatsuya, A.3
  • 24
    • 58449136038 scopus 로고    scopus 로고
    • A. Habrard, M. Inesta, D. Rizo, M. Sebban, Melody recognition with learned edit distances, in: Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2008 and SPR 2008, 2008, pp. 86-96.
    • A. Habrard, M. Inesta, D. Rizo, M. Sebban, Melody recognition with learned edit distances, in: Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2008 and SPR 2008, 2008, pp. 86-96.
  • 26
    • 76849083548 scopus 로고    scopus 로고
    • J. Eisner, Parameter estimation for probabilistic finite-state transducers, in: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL'02), Morristown, NJ, USA, 2001, pp. 1-8. doi: 〈http://dx.doi.org/http://dx.doi.org/10.3115/1073083.1073085〉.
    • J. Eisner, Parameter estimation for probabilistic finite-state transducers, in: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL'02), Morristown, NJ, USA, 2001, pp. 1-8. doi: 〈http://dx.doi.org/http://dx.doi.org/10.3115/1073083.1073085〉.
  • 28
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • Schlkopf B., Burges C., and Smola A. (Eds), MIT Press, Cambridge, MA
    • Joachims T. Making large-scale SVM learning practical. In: Schlkopf B., Burges C., and Smola A. (Eds). Advances in Kernel Methods-Support Vector Learning (1999), MIT Press, Cambridge, MA 169-184
    • (1999) Advances in Kernel Methods-Support Vector Learning , pp. 169-184
    • Joachims, T.1
  • 29
    • 56049098574 scopus 로고    scopus 로고
    • Sedil: Software for edit distance learning
    • Proceedings of the 19th European Conference on Machine Learning ECML, Springer, Berlin
    • L. Boyer, Y. Esposito, A. Habrard, J. Oncina, M. Sebban, Sedil: software for edit distance learning, in: Proceedings of the 19th European Conference on Machine Learning (ECML 2008), Lecture Notes in Computer Science, vol. 5212, Springer, Berlin, 2008, pp. 672-677.
    • (2008) Lecture Notes in Computer Science , vol.5212 , pp. 672-677
    • Boyer, L.1    Esposito, Y.2    Habrard, A.3    Oncina, J.4    Sebban, M.5
  • 30
    • 42749094100 scopus 로고    scopus 로고
    • Learning probabilistic models of tree edit distance
    • Bernard M., Boyer L., Habrard A., and Sebban M. Learning probabilistic models of tree edit distance. Pattern Recognition 41 8 (2008) 2611-2629
    • (2008) Pattern Recognition , vol.41 , Issue.8 , pp. 2611-2629
    • Bernard, M.1    Boyer, L.2    Habrard, A.3    Sebban, M.4


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