ei
Chiappa, S., Saigo, H., Tsuda, K.
A Bayesian Approach to Graph Regression with Relevant Subgraph Selection
In SIAM International Conference on Data Mining, pages: 295-304, (Editors: Park, H. , S. Parthasarathy, H. Liu), Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, SDM, May 2009 (inproceedings)
ei
Saigo, H., Tsuda, K.
Iterative Subgraph Mining for Principal Component Analysis
In ICDM 2008, pages: 1007-1012, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, IEEE International Conference on Data Mining, December 2008 (inproceedings)
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Saigo, H., Nowozin, S., Kadowaki, T., Kudo, T., Tsuda, K.
gBoost: A Mathematical Programming Approach to Graph Classification and Regression
Machine Learning, 75(1):69-89, November 2008 (article)
ei
Saigo, H., Krämer, N., Tsuda, K.
Partial Least Squares Regression for Graph Mining
In KDD2008, pages: 578-586, (Editors: Li, Y. , B. Liu, S. Sarawagi), ACM Press, New York, NY, USA, 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2008 (inproceedings)
ei
Saigo, H., Hattori, M., Tsuda, K.
Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)
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Kashima, H., Yamazaki, K., Saigo, H., Inokuchi, A.
Regression with Intervals
International Workshop on Data-Mining and Statistical Science (DMSS2007), October 2007, JSAI Incentive Award. Talk was given by Hisashi Kashima. (talk)
ei
Saigo, H., Uno, T., Tsuda, K.
Mining complex genotypic features
for predicting HIV-1 drug resistance
Bioinformatics, 23(18):2455-2462, September 2007 (article)
ei
Saigo, H., Kadowaki, T., Kudo, T., Tsuda, K.
Graph boosting for molecular QSAR analysis
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)
ei
Saigo, H., Kadowaki, T., Tsuda, K.
A Linear Programming Approach for Molecular QSAR analysis
In MLG 2006, pages: 85-96, (Editors: Gärtner, T. , G. C. Garriga, T. Meinl), International Workshop on Mining and Learning with Graphs, September 2006, Best Paper Award (inproceedings)
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Saigo, H., Vert, J., Akutsu, T.
Optimizing amino acid substitution matrices with a local alignment kernel
BMC Bioinformatics, 7(246):1-12, May 2006 (article)
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Danziger, S., Swamidass, S., Zeng, J., Dearth, L., Lu, Q., Cheng, J., Cheng, J., Hoang, V., Saigo, H., Luo, R., Baldi, P., Brachmann, R., Lathrop, R.
Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants
IEEE Transactions on Computational Biology and Bioinformatics, 3(2):114-125, April 2006 (article)
ei
Cheng, J., Saigo, H., Baldi, P.
Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching
Proteins, 62(3):617-629, February 2006 (article)
ei
Saigo, H.
Local Alignment Kernels for Protein Homology Detection
Biologische Kybernetik, Kyoto University, Kyoto, Japan, 2006 (phdthesis)
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Ralaivola, L., Swamidass, J., Saigo, H., Baldi, P.
Graph Kernels for Chemical Informatics
Neural Networks, 18(8):1093-1110, 2005 (article)
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Matsuda, S., Vert, J., Saigo, H., Ueda, N., Toh, H., Akutsu, T.
A novel representation of protein sequences for prediction of subcellular location using support vector machines
Protein Science, 14, pages: 2804-2813, 2005 (article)
ei
Vert, J., Saigo, H., Akutsu, T.
Local Alignment Kernels for Biological Sequences
In Kernel Methods in Computational Biology, pages: 131-153, MIT Press, Cambridge, MA,, 2004 (inbook)
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Saigo, H., Vert, J., Ueda, N., Akutsu, T.
Protein homology detection using string alignment kernels
Bioinformatics, 20(11):1682-1689, 2004 (article)