Canh Hao Nguyen
Bio-Knowledge Engineering Research Laboratory
Institute for Chemical Research, Kyoto University
Gokasho, Uji, Kyoto, 611-0011, Japan
Email: $myaccoutname @kuicr.kyoto-u.ac.jp
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.
- N. Wicker, C.H. Nguyen, H. Mamitsuka, "Some Properties of a Dissimilarity Measure for Labeled Graphs". Publications Mathematiques de Besancon. pp. 85-94, 2016.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- C. H. Nguyen and T. B. Ho, "An efficient kernel matrix evaluation measure," Pattern Recognition, vol. 41, no. 11, pp. 3366-3372, 2008.
- 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.
- C. H. Nguyen and T. B. Ho, "Kernel matrix evaluation," International Joint Conference on Artificial Intelligence (IJCAI2007), pp. 987-992, 2007.
- 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.
- 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.
- 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.
- 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.