Canh Hao Nguyen

Senior Lecturer

Bio-Knowledge Engineering Research Laboratory

Institute for Chemical Research, Kyoto University

Gokasho, Uji, Kyoto, 611-0011, Japan

Email: $myaccoutname @kuicr.kyoto-u.ac.jp

Research

I am interested in Machine Learning in/for Bioinformatics, specially Machine Learning on Graphs. I am working on models for underlying mechanisms of biological networks.

Publication

  1. L. Sun, C.H. Nguyen, H. Mamitsuka, "Fast and Robust Multi-View Multi-Task Learning via Group Sparsity", in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), to appear. pdf supplementary
  2. L. Sun, C.H. Nguyen, H. Mamitsuka, "Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning", in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), to appear. pdf supplementary
  3. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra". Bioinformatics 35, (Proceedings of the 26th International Conference on Intelligent Systems for Molecular Biology (ISMB 2019), pp. i164-i172 pdf
  4. H., Seki, C.H., Nguyen, V.-N., Huynh, M., Inuiguchi (Eds.) Integrated Uncertainty in Knowledge Modelling and Decision Making Proceedings of 7th International Symposium, IUKM 2019, Springer LNCS 11471, 2019. html
  5. N. Wicker, C.H. Nguyen, H. Mamitsuka, "A p-Laplacian random walk: application to video games". Accepted in Austrian Journal of Statistics, 2019. pdf
  6. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches". To appear in Briefings in Bioinformatics, 2018. pdf
  7. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "SIMPLE: Sparse Interaction Model over Peaks of MoLEcules for Fast, Interpretable Metabolite Identification from Tandem Mass Spectra".Bioinformatics, (Proceedings of the 26th International Conference on Intelligent Systems for Molecular Biology (ISMB 2018), pp. i323-i332, 2018. pdf
  8. N. Wicker, C.H. Nguyen, H. Mamitsuka, "Some Properties of a Dissimilarity Measure for Labeled Graphs". Publications Mathematiques de Besancon. pp. 85-94, 2016. pdf
  9. A. Mohamed, C.H. Nguyen, H. Mamitsuka, "NMRPro: An integrated web component for interactive processing and visualization of NMR spectra." Bioinformatics, vol. 32, no. 13, pp. 2067-2068, 2016. pdf
  10. C.H. Nguyen, H. Mamitsuka, "New Resistance Distances with Global Information on Large Graphs". JMLR Workshop and Conference Proceedings. Volume 51: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, pp. 639-647, May 2016. pdf supplementary
  11. A. Mohamed, C.H. Nguyen, H. Mamitsuka, "Current status and prospects of computational resources for natural product dereplication: A review" Briefings in Bioinformatics, vol. 17, no. 2, pp. 309-321, 2016. pdf
  12. A. Mohamed, T. Hancock, C.H. Nguyen, H. Mamitsuka, "NetPathMiner: R/Bioconductor package for network path mining through gene expression", Bioinformatics. vol. 30, no. 21, pp. 3139-3141, Nov 01, 2014. pdf
  13. C. H. Nguyen, N. Wicker and H. Mamitsuka, "Selecting Graph Cut Solutions via Global Graph Similarity", IEEE Transactions on Neural Networks and Learning Systems. vol. 25, no. 7, pp. 1407-1412, 2014. pdf
  14. N. Wicker, C. H. Nguyen and H. Mamitsuka, "A new dissimilarity measure for comparing labeled graphs", Linear Algebra and its Applications. vol. 438, no. 5, pp. 2331-2338. Mar 01, 2013. pdf
  15. C. H. Nguyen and H. Mamitsuka, "Latent Feature Kernels for Link Prediction on Sparse Graphs" IEEE Transactions on Neural Networks and Learning Systems. vo. 23, no. 11, pp. 1793-1804, 2012. pdf
  16. C. H. Nguyen and H. Mamitsuka, "Kernels for link prediction with latent feature models," The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2) (ECML/PKDD 2011), pp. 517-532, 2011. pdf
  17. C. H. Nguyen and H. Mamitsuka, "Discriminative graph embedding for label propagation," IEEE Transactions on Neural Networks, vol. 22, no. 9, pp. 1395-1405, 2011. pdf
  18. C. H. Nguyen, T. B. Ho, and V. Kreinovich, "Estimating quality of support vector machines learning under probabilistic and interval uncertainty: Algorithms and computational complexity," Interval / Probabilistic Uncertainty and Non-Classical Logics, pp. 57-69, 2008. pdf
  19. C. H. Nguyen and T. B. Ho, "An efficient kernel matrix evaluation measure," Pattern Recognition, vol. 41, no. 11, pp. 3366-3372, 2008. pdf
  20. H. Tanabe, T. B. Ho, C. H. Nguyen, and S. Kawasaki, "Simple but effective methods for combining kernels in computational biology," RIVF, pp. 71-78, 2008. pdf
  21. C. H. Nguyen and T. B. Ho, "Kernel matrix evaluation," International Joint Conference on Artificial Intelligence (IJCAI2007), pp. 987-992, 2007. pdf
  22. T. B. Ho, C. H. Nguyen, S. Kawasaki, S. Q. Le, and K. Takabayashi, "Exploiting temporal relations in mining hepatitis data," New Generation Computing, vol. 25, no. 3, pp. 247-262, 2007. pdf
  23. T. B. Ho, C. H. Nguyen, S. Kawasaki, and K. Takabayashi, "Temporal relations extraction in mining hepatitis data," The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2007), pp. 523-530, 2007.
  24. C. H. Nguyen and T. B. Ho, "Sampling for imbalanced data learning," The International Workshop on Data-Mining and Statistical Science (DMSS2006), pp. 12-19, 2006.
  25. C. H. Nguyen and T. B. Ho, "An imbalanced data rule learner," The European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2005), pp. 617-624, 2005. pdf