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Volumn , Issue , 2008, Pages 1-197

Kernels for Structured Data

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EID: 85131997221     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1142/6855     Document Type: Book
Times cited : (79)

References (186)
  • 2
    • 38149082722 scopus 로고    scopus 로고
    • Kernel fusion for image classification using fuzzy structural information
    • (b)
    • Aldea, E., Fouquier, G., Atif, J. and Bloch, I. (2007b). Kernel fusion for image classification using fuzzy structural information, in Advances in Visual Computing, pp. II: 307–317.
    • (2007) Advances in Visual Computing, Pp , vol.2 , pp. 307-317
    • Aldea, E.1    Fouquier, G.2    Atif, J.3    Bloch, I.4
  • 7
    • 0002469253 scopus 로고    scopus 로고
    • On learning from multi-instance examples: Empirical evalutaion of a theoretical approach
    • Morgan Kaufmann
    • Auer, P. (1997). On learning from multi-instance examples: Empirical evalutaion of a theoretical approach, in Proceedings of the 14th International Conference on Machine Learning (Morgan Kaufmann), pp. 21–29.
    • (1997) Proceedings of the 14Th International Conference on Machine Learning , pp. 21-29
    • Auer, P.1
  • 9
    • 77957549669 scopus 로고    scopus 로고
    • Graph kernels for molecular classification and prediction of mutagenicity, toxicity, and anti-cancer activity
    • Baldi, P. and Ralaivola, L. (2004). Graph kernels for molecular classification and prediction of mutagenicity, toxicity, and anti-cancer activity, Presentated at the Computational Biology Workshop of NIPS.
    • (2004) Presentated at the Computational Biology Workshop of NIPS
    • Baldi, P.1    Ralaivola, L.2
  • 11
    • 0001907967 scopus 로고    scopus 로고
    • Support vector machines: Hype or hallelujah?
    • Bennett, K. and Campbell, C. (2000). Support vector machines: Hype or hallelujah? SIGKDD Explorations 2, 2.
    • (2000) SIGKDD Explorations , vol.2 , Issue.2
    • Bennett, K.1    Campbell, C.2
  • 13
    • 0032069371 scopus 로고    scopus 로고
    • Top-down induction of first order logical decision trees
    • Blockeel, H. and De Raedt, L. (1998). Top-down induction of first order logical decision trees, Artificial Intelligence 101, 1-2, pp. 285–297.
    • (1998) Artificial Intelligence , vol.101 , Issue.1-2 , pp. 285-297
    • Blockeel, H.1    de Raedt, L.2
  • 14
    • 0031704194 scopus 로고    scopus 로고
    • A note on learning from multiple-instance examples
    • Blum, A. and Kalai, A. (1998). A note on learning from multiple-instance examples, Machine Learning 30, 1, pp. 23–29.
    • (1998) Machine Learning , vol.30 , Issue.1 , pp. 23-29
    • Blum, A.1    Kalai, A.2
  • 23
    • 85131971023 scopus 로고
    • Inexact graph matching for structural pattern recognition
    • Bunke, H. and Allerman, G. (1983). Inexact graph matching for structural pattern recognition, Pattern Recognition Letters 4.
    • (1983) Pattern Recognition Letters , pp. 4
    • Bunke, H.1    Allerman, G.2
  • 24
    • 38449122256 scopus 로고    scopus 로고
    • A family of novel graph kernels for structural pattern recognition
    • Bunke, H. and Riesen, K. (2007). A family of novel graph kernels for structural pattern recognition, in Iberoamerican Congress on Pattern Recognition, pp. 20–31.
    • (2007) Iberoamerican Congress on Pattern Recognition , pp. 20-31
    • Bunke, H.1    Riesen, K.2
  • 28
    • 84898995383 scopus 로고    scopus 로고
    • Convolution kernels for natural language
    • in T. G. Dietterich, S. Becker and Z. Ghahramani (eds.), MIT Press
    • Collins, M. and Duffy, N. (2002). Convolution kernels for natural language, in T. G. Dietterich, S. Becker and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems, Vol. 14 (MIT Press).
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Collins, M.1    Duffy, N.2
  • 30
    • 1942485292 scopus 로고    scopus 로고
    • On kernel methods for relational learning
    • Cumby, C. and Roth, D. (2003). On kernel methods for relational learning, in Proceedings of ICML03.
    • (2003) Proceedings of ICML03
    • Cumby, C.1    Roth, D.2
  • 31
    • 84947905415 scopus 로고
    • Inductive constraint logic
    • in K. Jantke, T. Shinohara and T. Zeugmann (eds.), LNAI, Vol., (Springer Ver-lag), ISBN 3-540-60454-5
    • De Raedt, L. and Van Laer, W. (1995). Inductive constraint logic, in K. Jantke, T. Shinohara and T. Zeugmann (eds.), Proceedings of the 6th International Workshop on Algorithmic Learning Theory, LNAI, Vol. 997 (Springer Ver-lag), ISBN 3-540-60454-5, pp. 80–94.
    • (1995) Proceedings of the 6Th International Workshop on Algorithmic Learning Theory , vol.997 , pp. 80-94
    • de Raedt, L.1    van Laer, W.2
  • 35
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • Dietterich, T. G., Lathrop, R. H. and Lozano-Pérez, T. (1997). Solving the multiple instance problem with axis-parallel rectangles, Artificial Intelligence 89, 1–2, pp. 31–71.
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.G.1    Lathrop, R.H.2    Lozano-Pérez, T.3
  • 37
    • 0013464438 scopus 로고    scopus 로고
    • Integrating experimentation and guidance in relational reinforcement learning
    • in C. Sammut and A. Hoffmann (eds.), Morgan Kaufmann Publishers, Inc
    • Driessens, K. and Džeroski, S. (2002). Integrating experimentation and guidance in relational reinforcement learning, in C. Sammut and A. Hoffmann (eds.), Proceedings of the Nineteenth International Conference on Machine Learning (Morgan Kaufmann Publishers, Inc), pp. 115–122, URL http://www.cs.kuleuven.ac.be/cgi-bin-dtai/publ\_info.pl?id=38%637.
    • (2002) Proceedings of the Nineteenth International Conference on Machine Learning , pp. 115-122
    • Driessens, K.1    Džeroski, S.2
  • 39
    • 84948172455 scopus 로고    scopus 로고
    • Speeding up relational reinforcement learning through the use of an incremental first order decision tree learner
    • in L. De Raedt and P. Flach (eds.), Vol, Springer-Verlag
    • Driessens, K., Ramon, J. and Blockeel, H. (2001). Speeding up relational reinforcement learning through the use of an incremental first order decision tree learner, in L. De Raedt and P. Flach (eds.), Proceedings of the 13th European Conference on Machine Learning, Lecture Notes in Artificial Intelligence, Vol. 2167 (Springer-Verlag), pp. 97–108.
    • (2001) Proceedings of the 13Th European Conference on Machine Learning, Lecture Notes in Artificial Intelligence , vol.2167 , pp. 97-108
    • Driessens, K.1    Ramon, J.2    Blockeel, H.3
  • 44
    • 0031338770 scopus 로고    scopus 로고
    • Distance measures for point sets and their computation
    • Eiter, T. and Mannila, H. (1997). Distance measures for point sets and their computation, Acta Informatica 34.
    • (1997) Acta Informatica , vol.34
    • Eiter, T.1    Mannila, H.2
  • 46
    • 38349114038 scopus 로고    scopus 로고
    • Genome scale enzyme metabolite and drug target interaction predictions using the signature molecular descriptor
    • Faulon, J. L., Misra, M., Martin, S., Sale, K. and Sapra, R. (2008). Genome scale enzyme metabolite and drug target interaction predictions using the signature molecular descriptor, Bioinformatics 24, p. 225.
    • (2008) Bioinformatics , vol.24 , pp. 225
    • Faulon, J.L.1    Misra, M.2    Martin, S.3    Sale, K.4    Sapra, R.5
  • 49
    • 1942421135 scopus 로고    scopus 로고
    • The geometry of ROC space: Understanding machine learning metrics through ROC isometrics
    • AAAI Press
    • Flach, P. A. (2003). The geometry of ROC space: understanding machine learning metrics through ROC isometrics, in Proc. 20th International Conference on Machine Learning (AAAI Press).
    • (2003) Proc. 20Th International Conference on Machine Learning
    • Flach, P.A.1
  • 52
    • 1942419282 scopus 로고    scopus 로고
    • Representations for learning control policies
    • in E. de Jong and T. Oates (eds.), The University of New South Wales, Sydney
    • Forbes, J. and Andre, D. (2002). Representations for learning control policies, in E. de Jong and T. Oates (eds.), Proceedings of the ICML-2002 Workshop on Development of Representations (The University of New South Wales, Sydney), pp. 7–14.
    • (2002) Proceedings of the ICML-2002 Workshop on Development of Representations , pp. 7-14
    • Forbes, J.1    Andre, D.2
  • 59
    • 44449107147 scopus 로고    scopus 로고
    • Support-vector-machine-based ranking significantly improves the effectiveness of similarity searching using 2d fingerprints and multiple reference compounds
    • Geppert, H., Horváth, T., Gärtner, T., Wrobel, S. and Bajorath, J. (2008). Support-vector-machine-based ranking significantly improves the effectiveness of similarity searching using 2d fingerprints and multiple reference compounds, Journal of Chemical Information and Modeling.
    • (2008) Journal of Chemical Information and Modeling
    • Geppert, H.1    Horváth, T.2    Gärtner, T.3    Wrobel, S.4    Bajorath, J.5
  • 60
    • 0001330098 scopus 로고
    • A general coefficient of similarity and some of its properties
    • Gower, J. C. (1971). A general coefficient of similarity and some of its properties, Biometrics 27, pp. 857–871.
    • (1971) Biometrics , vol.27 , pp. 857-871
    • Gower, J.C.1
  • 63
    • 85131973291 scopus 로고
    • Probability, Random Processes, and Ergodic Properties (Springer-Verlag)
    • Gray, R. M. (1987). Probability, Random Processes, and Ergodic Properties (Springer-Verlag).
    • (1987)
    • Gray, R.M.1
  • 65
    • 0004019973 scopus 로고    scopus 로고
    • Tech. rep., Department of Computer Science, University of California at Santa Cruz
    • Haussler, D. (1999). Convolution kernels on discrete structures, Tech. rep., Department of Computer Science, University of California at Santa Cruz.
    • (1999) Convolution Kernels on Discrete Structures
    • Haussler, D.1
  • 73
    • 15844372451 scopus 로고    scopus 로고
    • Svm learning with the schur–hadamard inner product for graphs
    • Jain, B. J., Geibel, P. and Wysotzki, F. (2005). Svm learning with the schur–hadamard inner product for graphs, Neurocomputing 64, pp. 93–105.
    • (2005) Neurocomputing , vol.64 , pp. 93-105
    • Jain, B.J.1    Geibel, P.2    Wysotzki, F.3
  • 74
    • 0002714543 scopus 로고    scopus 로고
    • Making large–scale SVM learning practical
    • in B. Schölkopf, C. J. C. Burges and A. J. Smola (eds.), MIT Press
    • Joachims, T. (1999). Making large–scale SVM learning practical, in B. Schölkopf, C. J. C. Burges and A. J. Smola (eds.), Advances in Kernel Methods — Support Vector Learning (MIT Press).
    • (1999) Advances in Kernel Methods — Support Vector Learning
    • Joachims, T.1
  • 77
    • 20444410410 scopus 로고    scopus 로고
    • Virtual screening of molecular databases using a support vector machine
    • Jorissen, R. N. and Gilson, M. K. (2005). Virtual screening of molecular databases using a support vector machine, Journal of Chemical Information and Modeling 45, 3, pp. 549–561.
    • (2005) Journal of Chemical Information and Modeling , vol.45 , Issue.3 , pp. 549-561
    • Jorissen, R.N.1    Gilson, M.K.2
  • 80
    • 0036166451 scopus 로고    scopus 로고
    • Classifying g-protein coupled receptors with support vector machines
    • Karchin, R., Karplus, K. and Haussler, D. (2002). Classifying g-protein coupled receptors with support vector machines, Bioinformatics 18, 1, pp. 147–159.
    • (2002) Bioinformatics , vol.18 , Issue.1 , pp. 147-159
    • Karchin, R.1    Karplus, K.2    Haussler, D.3
  • 83
    • 0011858375 scopus 로고
    • Integrated segmentation and recognition of hand-printed numerals
    • in R. Lippmann, J. Moody and D. Touretzky (eds.), Morgan Kaufmann
    • Keeler, J. D., Rumelhart, D. E. and Leow, W.-K. (1991). Integrated segmentation and recognition of hand-printed numerals, in R. Lippmann, J. Moody and D. Touretzky (eds.), Advances in Neural Information Processing Systems, Vol. 3 (Morgan Kaufmann), pp. 557–563.
    • (1991) Advances in Neural Information Processing Systems , vol.3 , pp. 557-563
    • Keeler, J.D.1    Rumelhart, D.E.2    Leow, W.-K.3
  • 84
    • 84898963616 scopus 로고    scopus 로고
    • Efficiency versus convergence of boolean kernels for on-line learning algorithms
    • in T. Dietterich, S. Becker and Z. Ghahramani (eds.), MIT Press
    • Khardon, R., Roth, D. and Servedio, R. (2002). Efficiency versus convergence of boolean kernels for on-line learning algorithms, in T. Dietterich, S. Becker and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems, Vol. 14 (MIT Press).
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Khardon, R.1    Roth, D.2    Servedio, R.3
  • 89
    • 85131994588 scopus 로고
    • Elements of the Theory of Functions and Functional Analysis: Measure
    • (a), Academic Press
    • Kolmogorov, A. N. and Fomin, S. V. (1960a). Elements of the Theory of Functions and Functional Analysis: Measure, Lebesgue Integrals, and Hilbert Space, Vol. 2 (Academic Press).
    • (1960) Lebesgue Integrals, and Hilbert Space , vol.2
    • Kolmogorov, A.N.1    Fomin, S.V.2
  • 91
    • 0041775676 scopus 로고    scopus 로고
    • Diffusion kernels on graphs and other discrete input spaces
    • in C. Sammut and A. Hoffmann (eds.), Morgan Kaufmann
    • Kondor, R. I. and Lafferty, J. (2002). Diffusion kernels on graphs and other discrete input spaces, in C. Sammut and A. Hoffmann (eds.), Proceedings of the 19th International Conference on Machine Learning (Morgan Kaufmann), pp. 315–322.
    • (2002) Proceedings of the 19Th International Conference on Machine Learning , pp. 315-322
    • Kondor, R.I.1    Lafferty, J.2
  • 101
    • 84898968688 scopus 로고    scopus 로고
    • Mismatch string kernels for SVM protein classification
    • in S. Becker, S. Thrun and K. Obermayer (eds.), MIT Press
    • Leslie, C., Eskin, E., Weston, J. and Noble, W. (2003). Mismatch string kernels for SVM protein classification, in S. Becker, S. Thrun and K. Obermayer (eds.), Advances in Neural Information Processing Systems, Vol. 15 (MIT Press).
    • (2003) Advances in Neural Information Processing Systems , vol.15
    • Leslie, C.1    Eskin, E.2    Weston, J.3    Noble, W.4
  • 109
    • 84898935332 scopus 로고    scopus 로고
    • A framework for multiple-instance learning
    • in M. I. Jordan, M. J. Kearns and S. A. Solla (eds.), MIT Press
    • Maron, O. and Lozano-Pérez, T. (1998). A framework for multiple-instance learning, in M. I. Jordan, M. J. Kearns and S. A. Solla (eds.), Advances in Neural Information Processing Systems, Vol. 10 (MIT Press).
    • (1998) Advances in Neural Information Processing Systems , vol.10
    • Maron, O.1    Lozano-Pérez, T.2
  • 117
    • 34147162188 scopus 로고    scopus 로고
    • A convolution edit kernel for error-tolerant graph matching
    • (a)
    • Neuhaus, M. and Bunke, H. (2006a). A convolution edit kernel for error-tolerant graph matching, in International Conference on Pattern Recognition, pp. IV: 220–223.
    • (2006) International Conference on Pattern Recognition , vol.4 , pp. 220-223
    • Neuhaus, M.1    Bunke, H.2
  • 119
    • 0032163862 scopus 로고    scopus 로고
    • Solving ill-conditioned and singular linear systems: A tutorial on regularization
    • Neumaier, A. (1998). Solving ill-conditioned and singular linear systems: A tutorial on regularization, SIAM Review 40, 3, pp. 636–666, URL http://dx.doi.org/10.1137/S0036144597321909.
    • (1998) SIAM Review , vol.40 , Issue.3 , pp. 636-666
    • Neumaier, A.1
  • 121
    • 85131989353 scopus 로고    scopus 로고
    • Probabilistic reasoning in a classical logic
    • To appear
    • Ng, K. and Lloyd, J. W. (2008). Probabilistic reasoning in a classical logic, Journal of Applied Logic To appear.
    • (2008) Journal of Applied Logic
    • Ng, K.1    Lloyd, J.W.2
  • 123
    • 0036832956 scopus 로고    scopus 로고
    • Kernel-based reinforcement learning
    • Ormoneit, D. and Sen, S. (2002). Kernel-based reinforcement learning, Machine Learning 49, pp. 161–178.
    • (2002) Machine Learning , vol.49 , pp. 161-178
    • Ormoneit, D.1    Sen, S.2
  • 128
    • 32044451133 scopus 로고    scopus 로고
    • Distribution-based aggregation for relational learning with identifier attributes
    • Perlich, C. and Provost, F. (2006). Distribution-based aggregation for relational learning with identifier attributes, Mach. Learn. 62, pp. 65–105, URL http://portal.acm.org/citation.cfm?id=1113913.
    • (2006) Mach. Learn. , vol.62 , pp. 65-105
    • Perlich, C.1    Provost, F.2
  • 129
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • in B. Schölkopf, C. J. C. Burges and A. J. Smola (eds.), MIT Press
    • Platt, J. C. (1999). Fast training of support vector machines using sequential minimal optimization, in B. Schölkopf, C. J. C. Burges and A. J. Smola (eds.), Advances in kernel methods: support vector learning (MIT Press).
    • (1999) Advances in Kernel Methods: Support Vector Learning
    • Platt, J.C.1
  • 130
    • 85131994806 scopus 로고    scopus 로고
    • The mathematics of learning: Dealing with data
    • Poggio and Smale (2003). The mathematics of learning: Dealing with data, Notices of the American Mathematical Society 50.
    • (2003) Notices of the American Mathematical Society , pp. 50
  • 131
    • 0003266620 scopus 로고    scopus 로고
    • Robust classification for imprecise environments
    • Provost, F. and Fawcett, T. (2000). Robust classification for imprecise environments, Machine Learing 42, 3.
    • (2000) Machine Learing , vol.42 , pp. 3
    • Provost, F.1    Fawcett, T.2
  • 133
    • 0001172265 scopus 로고
    • Learning logical definitions from relations
    • Quinlan, J. R. (1990). Learning logical definitions from relations. Machine Learning 5, 3, pp. 239–266.
    • (1990) Machine Learning , vol.5 , Issue.3 , pp. 239-266
    • Quinlan, J.R.1
  • 134
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE 77, 2, pp. 257–285.
    • (1989) Proceedings of the IEEE , vol.77 , Issue.2 , pp. 257-285
    • Rabiner, L.R.1
  • 135
  • 137
    • 26944487064 scopus 로고    scopus 로고
    • Expressivity versus efficiency of graph kernels, in First International Workshop on Mining Graphs
    • Ramon, J. and Gärtner, T. (2003). Expressivity versus efficiency of graph kernels, in First International Workshop on Mining Graphs, Trees and Sequences.
    • (2003) Trees and Sequences
    • Ramon, J.1    Gärtner, T.2
  • 138
    • 0016523213 scopus 로고
    • Bounds on backtrack algorithms for listing cycles, paths, and spanning trees
    • Read, R. C. and Tarjan, R. E. (1975). Bounds on backtrack algorithms for listing cycles, paths, and spanning trees, Networks 5, 3, pp. 237–252.
    • (1975) Networks , vol.5 , Issue.3 , pp. 237-252
    • Read, R.C.1    Tarjan, R.E.2
  • 142
    • 84948143092 scopus 로고    scopus 로고
    • Learning of boolean functions using support vector machines
    • in N. Abe, R. Khardon and T. Zeugmann (eds.), Springer-Verlag
    • Sadohara, K. (2001). Learning of boolean functions using support vector machines, in N. Abe, R. Khardon and T. Zeugmann (eds.), Proceedings of the 12th Conference on Algorithmic Learning Theory (Springer-Verlag), pp. 106–118.
    • (2001) Proceedings of the 12Th Conference on Algorithmic Learning Theory , pp. 106-118
    • Sadohara, K.1
  • 145
    • 84898957207 scopus 로고    scopus 로고
    • String kernels, fisher kernels and finite state automata
    • in S. Becker, S. Thrun and K. Obermayer (eds.), MIT Press
    • Saunders, C., Shawe-Taylor, J. and Vinokourov, A. (2003). String kernels, fisher kernels and finite state automata, in S. Becker, S. Thrun and K. Obermayer (eds.), Advances in Neural Information Processing Systems, Vol. 15 (MIT Press).
    • (2003) Advances in Neural Information Processing Systems , vol.15
    • Saunders, C.1    Shawe-Taylor, J.2    Vinokourov, A.3
  • 152
    • 84898996216 scopus 로고    scopus 로고
    • Speech recognition using SVMs
    • in T. Dietterich, S. Becker and Z. Ghahramani (eds.), MIT Press
    • Smith, N. and Gales, M. (2002). Speech recognition using SVMs, in T. Dietterich, S. Becker and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems, Vol. 14 (MIT Press).
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Smith, N.1    Gales, M.2
  • 156
    • 0030212927 scopus 로고    scopus 로고
    • Theories for mutagenicity: A study in first-order and feature-based induction
    • Srinivasan, A., Muggleton, S. H., Sternberg, M. J. E. and King, R. (1996). Theories for mutagenicity: a study in first-order and feature-based induction, Artificial Intelligence 85, pp. 277–299.
    • (1996) Artificial Intelligence , vol.85 , pp. 277-299
    • Srinivasan, A.1    Muggleton, S.H.2    Sternberg, M.J.E.3    King, R.4
  • 158
    • 0033742076 scopus 로고    scopus 로고
    • Least squares support vector machines for classification and nonlinear modelling
    • Suykens, J. A. K. (2000). Least squares support vector machines for classification and nonlinear modelling, Neural Network World 10.
    • (2000) Neural Network World , vol.10
    • Suykens, J.A.K.1
  • 159
    • 26944486424 scopus 로고    scopus 로고
    • Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
    • Swamidass, S. J., Chen, J., Bruand, J., Phung, P., Ralaivola, L. and Baldi, P. (2005). Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity, Bioinformatics 21, pp. i359–i368.
    • (2005) Bioinformatics , vol.21 , pp. i359-i368
    • Swamidass, S.J.1    Chen, J.2    Bruand, J.3    Phung, P.4    Ralaivola, L.5    Baldi, P.6
  • 160
    • 34047252819 scopus 로고    scopus 로고
    • University of Auckland Lecture Notes
    • Tan, S. M. and Fox, C. (2005). Inverse problems, University of Auckland Lecture Notes.
    • (2005) Inverse Problems
    • Tan, S.M.1    Fox, C.2
  • 162
    • 0001300994 scopus 로고
    • Solution of incorrectly formulated problems and the regularization method
    • Tikhonov, A. N. (1963). Solution of incorrectly formulated problems and the regularization method, Soviet Math. Dokl. 4, pp. 1035–1038.
    • (1963) Soviet Math. Dokl. , vol.4 , pp. 1035-1038
    • Tikhonov, A.N.1
  • 167
    • 0032594959 scopus 로고    scopus 로고
    • An overview of statistical learning theory
    • Vapnik, V. N. (1999). An overview of statistical learning theory, IEEE Transaction on Neural Networks 10, 5, p. 988.
    • (1999) IEEE Transaction on Neural Networks , vol.10 , Issue.5 , pp. 988
    • Vapnik, V.N.1
  • 168
    • 11244331236 scopus 로고    scopus 로고
    • A tree kernel to analyse phylogenetic profiles
    • Vert, J.-P. (2002). A tree kernel to analyse phylogenetic profiles, in ISMB (Sup-plement of Bioinformatics), pp. 276–284.
    • (2002) ISMB (Sup-Plement of Bioinformatics) , pp. 276-284
    • Vert, J.-P.1
  • 169
    • 84899021874 scopus 로고    scopus 로고
    • Graph driven features extraction from mi-croarray data using diffusion kernels and kernel CCA
    • in S. Becker, S. Thrun and K. Obermayer (eds.), MIT Press
    • Vert, J.-P. and Kanehisa, M. (2003). Graph driven features extraction from mi-croarray data using diffusion kernels and kernel CCA, in S. Becker, S. Thrun and K. Obermayer (eds.), Advances in Neural Information Processing Systems, Vol. 15 (MIT Press).
    • (2003) Advances in Neural Information Processing Systems , vol.15
    • Vert, J.-P.1    Kanehisa, M.2
  • 171
    • 84898962121 scopus 로고    scopus 로고
    • Fast kernels for string and tree matching
    • in S. Becker, S. Thrun and K. Obermayer (eds.), MIT Press
    • Vishwanathan, S. V. N. and Smola, A. J. (2003). Fast kernels for string and tree matching, in S. Becker, S. Thrun and K. Obermayer (eds.), Advances in Neural Information Processing Systems, Vol. 15 (MIT Press).
    • (2003) Advances in Neural Information Processing Systems , vol.15
    • Vishwanathan, S.V.N.1    Smola, A.J.2
  • 173
    • 33846637208 scopus 로고    scopus 로고
    • Binet-cauchy kernels on dynamical systems and its application to the analysis of dynamic scenes
    • Vishwanathan, S. V. N., Smola, A. J. and Vidal, R. (2007b). Binet-cauchy kernels on dynamical systems and its application to the analysis of dynamic scenes, International Journal of Computer Vision 73, pp. 95–119.
    • (2007) International Journal of Computer Vision , vol.73 , pp. 95-119
    • Vishwanathan, S.V.N.1    Smola, A.J.2    Vidal, R.3
  • 178
    • 0004202459 scopus 로고    scopus 로고
    • Tech. rep., Department of Computer Science, Royal Holloway, University of London
    • Watkins, C. (1999a). Dynamic alignment kernels, Tech. rep., Department of Computer Science, Royal Holloway, University of London.
    • (1999) Dynamic Alignment Kernels
    • Watkins, C.1
  • 179
    • 0142227382 scopus 로고    scopus 로고
    • Tech. rep., Department of Computer Science, Royal Holloway, University of London
    • Watkins, C. (1999b). Kernels from matching operations, Tech. rep., Department of Computer Science, Royal Holloway, University of London.
    • (1999) Kernels from Matching Operations
    • Watkins, C.1
  • 185
    • 84898999828 scopus 로고    scopus 로고
    • EM-DD: An improved multiple-instance learning technique
    • in T. Dietterich, S. Becker and Z. Ghahramani (eds.), MIT Press
    • Zhang, Q. and Goldman, S. (2002). EM-DD: An improved multiple-instance learning technique, in T. Dietterich, S. Becker and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems, Vol. 14 (MIT Press).
    • (2002) Advances in Neural Information Processing Systems , vol.14
    • Zhang, Q.1    Goldman, S.2
  • 186
    • 0033670134 scopus 로고    scopus 로고
    • Engineering support vector machine kernels that recognize translation initiation sites
    • Zien, A., Ratsch, G., Mika, S., Schölkopf, B., Lengauer, T. and Muller, K.-R. (2000). Engineering support vector machine kernels that recognize translation initiation sites, Bioinformatics 16, 9, pp. 799–807.
    • (2000) Bioinformatics , vol.16 , Issue.9 , pp. 799-807
    • Zien, A.1    Ratsch, G.2    Mika, S.3    Schölkopf, B.4    Lengauer, T.5    Muller, K.-R.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.