Combining recurrent neural networks and support vector machines for structural pattern recognition

Brijnesh J. Jain; Peter Geibel; Fritz Wysotzki

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Combining recurrent neural networks and support vector machines for structural pattern recognition

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 3238 LNAI 241-255

DOI: 10.1007/978-3-540-30221-6_19

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Abstract

We apply support vector learning to attributed graphs where the kernel matrices are based on approximations of the Schur-Hadamard (SH) inner product by means of recurrent neural networks. We present and discuss experimental results of different classifiers constructed by a SVM operating on positive semi-definite (psd) and non-psd kernel matrices. © 2004 Springer-Verlag.

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Jain, B. J., Geibel, P., & Wysotzki, F. (2004). Combining recurrent neural networks and support vector machines for structural pattern recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3238 LNAI, pp. 241–255). Springer Verlag. https://doi.org/10.1007/978-3-540-30221-6_19

Combining recurrent neural networks and support vector machines for structural pattern recognition

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