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Koji Tsuda: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Volker Roth, Koji Tsuda
    Pairwise Coupling for Machine Recognition of Hand-Printed Japanese Characters. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2001, pp:1120-1125 [Conf]
  2. Gökhan H. Bakir, Alexander Zien, Koji Tsuda
    Learning to Find Graph Pre-images. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:253-261 [Conf]
  3. Masanori Arita, Koji Tsuda, Kiyoshi Asai
    Modeling splicing sites with pairwise correlations. [Citation Graph (0, 0)][DBLP]
    ECCB, 2002, pp:27-34 [Conf]
  4. Koji Tsuda, HyunJung Shin, Bernhard Schölkopf
    Fast protein classification with multiple networks. [Citation Graph (0, 0)][DBLP]
    ECCB/JBI, 2005, pp:65- [Conf]
  5. Koji Tsuda
    Support vector classifier with asymetric kernel function. [Citation Graph (0, 0)][DBLP]
    ESANN, 1999, pp:183-188 [Conf]
  6. Koji Tsuda, Motoaki Kawanabe
    The Leave-One-Out Kernel. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:727-732 [Conf]
  7. Koji Tsuda, Gunnar Rätsch, Sebastian Mika, Klaus-Robert Müller
    Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:331-338 [Conf]
  8. Koji Tsuda, Michihiko Minoh
    A Nonparametric Density Model for Classification in a High Dimensional Space. [Citation Graph (0, 0)][DBLP]
    ICDAR, 1997, pp:1082-1087 [Conf]
  9. Koji Tsuda, Shuji Senda, Michihiko Minoh, Katsuo Ikeda
    Clustering OCR-ed texts for browsing document image database. [Citation Graph (0, 0)][DBLP]
    ICDAR, 1995, pp:171-174 [Conf]
  10. Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
    Marginalized Kernels Between Labeled Graphs. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:321-328 [Conf]
  11. Koji Tsuda
    Propagating distributions on a hypergraph by dual information regularization. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:920-927 [Conf]
  12. Koji Tsuda, Taku Kudo
    Clustering graphs by weighted substructure mining. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:953-960 [Conf]
  13. Koji Tsuda, Shotaro Akaho
    Large Margin Classifier via Semiparametric Inference. [Citation Graph (0, 0)][DBLP]
    IJCNN (2), 2000, pp:23-28 [Conf]
  14. Koji Tsuda, Taishin Kin, Kiyoshi Asai
    Marginalized kernels for biological sequences. [Citation Graph (0, 0)][DBLP]
    ISMB, 2002, pp:268-275 [Conf]
  15. Koji Tsuda, William Stafford Noble
    Learning kernels from biological networks by maximizing entropy. [Citation Graph (0, 0)][DBLP]
    ISMB/ECCB (Supplement of Bioinformatics), 2004, pp:326-333 [Conf]
  16. Hideya Yoshiuchi, Koji Tsuda, Shigenobu Fukushima, Michihiko Minoh
    Pattern Recognition Method for Metric Space by Four Points Embedding. [Citation Graph (0, 0)][DBLP]
    IVCNZ, 1998, pp:186-191 [Conf]
  17. Koji Tsuda, Motoaki Kawanabe, Klaus-Robert Müller
    Clustering with the Fisher Score. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:729-736 [Conf]
  18. Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller
    A New Discriminative Kernel From Probabilistic Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:977-984 [Conf]
  19. Koji Tsuda, Gunnar Rätsch
    Image Reconstruction by Linear Programming. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  20. Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth
    Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  21. Tsuyoshi Kato, Koji Tsuda, Kentaro Tomii, Kiyoshi Asai
    A New Variational Framework for Rigid-Body Alignment. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2004, pp:171-179 [Conf]
  22. Tsuyoshi Kato, Koji Tsuda, Kiyoshi Asai
    Selective integration of multiple biological data for supervised network inference. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:10, pp:2488-2495 [Journal]
  23. Yasuo Tabei, Koji Tsuda, Taishin Kin, Kiyoshi Asai
    SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:14, pp:1723-1729 [Journal]
  24. Michiaki Hamada, Koji Tsuda, Taku Kudo, Taishin Kin, Kiyoshi Asai
    Mining frequent stem patterns from unaligned RNA sequences. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2006, v:22, n:20, pp:2480-2487 [Journal]
  25. Koji Tsuda, Shotaro Akaho, Kiyoshi Asai
    Approximating Incomplete Kernel Matrices by the em Algorithm [Citation Graph (0, 0)][DBLP]
    CoRR, 2002, v:0, n:, pp:- [Journal]
  26. Koji Tsuda, Shotaro Akaho, Kiyoshi Asai
    The em Algorithm for Kernel Matrix Completion with Auxiliary Data. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2003, v:4, n:, pp:67-81 [Journal]
  27. Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth
    Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:995-1018 [Journal]
  28. Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe, Klaus-Robert Müller
    Asymptotic Properties of the Fisher Kernel. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:1, pp:115-137 [Journal]
  29. Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller
    A New Discriminative Kernel from Probabilistic Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:10, pp:2397-2414 [Journal]
  30. Koji Tsuda, Shinsuke Uda, Taishin Kin, Kiyoshi Asai
    Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2004, v:19, n:1, pp:63-72 [Journal]
  31. Koji Tsuda
    Subspace classifier in the Hilbert space. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1999, v:20, n:5, pp:513-519 [Journal]
  32. Koji Tsuda, Michihiko Minoh, Katsuo Ikeda
    Extracting straight lines by sequential fuzzy clustering. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1996, v:17, n:6, pp:643-649 [Journal]
  33. Koji Tsuda
    The subspace method in Hilbert space. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2001, v:32, n:6, pp:55-61 [Journal]
  34. Koji Tsuda, Shuji Senda, Michihiko Minoh, Katsuo Ikeda
    Sequential fuzzy cluster extraction and its robustness against noise. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 1997, v:28, n:6, pp:10-17 [Journal]
  35. Koji Tsuda, Gunnar Rätsch
    Image reconstruction by linear programming. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Image Processing, 2005, v:14, n:6, pp:737-744 [Journal]
  36. Shigeru Muraki, Toshiharu Nakai, Yasuyo Kita, Koji Tsuda
    An Attempt for Coloring Multichannel MR Imaging Data. [Citation Graph (0, 0)][DBLP]
    IEEE Trans. Vis. Comput. Graph., 2001, v:7, n:3, pp:265-274 [Journal]
  37. Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir
    Weighted Substructure Mining for Image Analysis. [Citation Graph (0, 0)][DBLP]
    CVPR, 2007, pp:- [Conf]
  38. Koji Tsuda
    Entire regularization paths for graph data. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:919-926 [Conf]
  39. Tsuyoshi Idé, Koji Tsuda
    Change-Point Detection using Krylov Subspace Learning. [Citation Graph (0, 0)][DBLP]
    SDM, 2007, pp:- [Conf]

  40. Discriminative Subsequence Mining for Action Classification. [Citation Graph (, )][DBLP]


  41. Iterative Subgraph Mining for Principal Component Analysis. [Citation Graph (, )][DBLP]


  42. Frequent Subgraph Retrieval in Geometric Graph Databases. [Citation Graph (, )][DBLP]


  43. Partial least squares regression for graph mining. [Citation Graph (, )][DBLP]


  44. Multi-way set enumeration in real-valued tensors. [Citation Graph (, )][DBLP]


  45. On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. [Citation Graph (, )][DBLP]


  46. Graph Mining with Variational Dirichlet Process Mixture Models. [Citation Graph (, )][DBLP]


  47. Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. [Citation Graph (, )][DBLP]


  48. A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection. [Citation Graph (, )][DBLP]


  49. Weighted Substructure Mining for Image Analysis. [Citation Graph (, )][DBLP]


  50. Mining complex genotypic features for predicting HIV-1 drug resistance. [Citation Graph (, )][DBLP]


  51. The DICS repository: module-assisted analysis of disease-related gene lists. [Citation Graph (, )][DBLP]


  52. Enumeration of condition-dependent dense modules in protein interaction networks. [Citation Graph (, )][DBLP]


  53. Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. [Citation Graph (, )][DBLP]


  54. Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. [Citation Graph (, )][DBLP]


  55. NIPS workshop on New Problems and Methods in Computational Biology. [Citation Graph (, )][DBLP]


  56. Mining expression-dependent modules in the human interaction network. [Citation Graph (, )][DBLP]


  57. Network-based de-noising improves prediction from microarray data. [Citation Graph (, )][DBLP]


  58. Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. [Citation Graph (, )][DBLP]


  59. Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method [Citation Graph (, )][DBLP]


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