Publications

Recent Tecnical Reports

  1. Yamada, M., Suzuki, T., Kanamori, T., Hachiya, H., & Sugiyama, M.
    Relative Density-Ratio Estimation for Robust Distribution Comparison.
    arXiv:1106.4729. [paper]

Conference Papers (full review)

  1. Yamada, M., Sigal, L., & Raptis, M.
    No Bias Left Behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation.
    In proceedings of European Conference on Computer Vision (ECCV2012), pp.xxx-xxx 2012. to appear

  2. Niu, G., Dai, B., Yamada, M., & Sugiyama, M..
    Information-theoretic Semi-supervised Metric Learning via Entropy Regularization.
    In proceedings of 29th International Conference on Machine Learning (ICML2012), pp.xxx-xxx, Edinburgh, Scotland, Jun. 26-Jul. 1. to appear.

  3. Sugiyama, M., Hachiya, H., Yamada, M., Simm, J., & Nam, H.
    Least-squares probabilistic classifier: A computationally efficient alternative to kernel logistic regression.
    In Proceedings of International Workshop on Statistical Machine Learning for Speech Processing (IWSML2012), pp.1-10, Kyoto, Japan, Mar. 31, 2012.

  4. Yamada, M., Suzuki, T., Kanamori, T., Hachiya, H., & Sugiyama, M.
    Relative Density-Ratio Estimation for Robust Distribution Comparison.
    Advances in Neural Information Processing Systems (NIPS2011), pp.594-602, 2011.

  5. Yamada, M., Niu, G., Takagi, J. & Sugiyama, M.
    Computationally efficient sufficient dimension reduction via squared-loss mutual information.
    In C.-N. Hsu and W. S. Lee (Eds.), Proceedings of the Third Asian Conference on Machine Learning (ACML2011), JMLR Workshop and Conference Proceedings, vol.20, pp.247-262, Taoyuan, Taiwan, Nov. 13-15, 2011.
    [paper]

  6. Yamada, M. & Sugiyama, M.
    Direct Density-Ratio Estimation with Dimensionality Reduction via Hetero-Distributional Subspace Analysis.
    In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11), pp.549-554, San Francisco, California, U.S.A, Aug. 7-11, 2011.

  7. Sugiyama, M., Yamada, M. Kimura, M. & Hachiya, H.
    On information-maximization clustering: tuning parameter selection and analytic solution.
    In Proceedings of 28th International Conference on Machine Learning (ICML2011), pp.65-72, Bellevue, Washington, Jun. 28- Jul. 2, 2011.

  8. Yamada, M. & Sugiyama, M.
    Cross-Domain Object Matching with Model Selection.
    In Proceedings of Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS2011), to appear. [paper, software]

  9. Takagi, J., Ohishi, Y., Kimura, A., Sugiyama, M., Yamada, M., & Kameoka H.
    Automatic Audio Tag Classification via Semi-Supervised Canonical Density Estimation.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2011), pp.2232-2235, Prague, Czech Republic, May 22-27, 2011.

  10. Yamada, M. & Sugiyama, M.
    Dependence Minimizing Regression with Model Selection for Non-Linear Causal Inference under Non-Gaussian Noise.
    In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), pp.643-648, Atlanta, Georgia, U.S.A, Jul. 11-15, 2010. [software]

  11. Yamada, M., Sugiyama, M., & Wichern, G.
    Direct Importance Estimation with Probabilistic Principal Component Analyzers.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2010), pp.1962-1965, Dallas, Texas, USA, Mar. 14-19, 2010.

  12. Yamada, M., Sugiyama, M., Wichern, G., & Matsui, T.
    Acceleration of Sequence Kernel Computation for Real-Time Speaker Identification.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2010), pp.1626-1629, Dallas, Texas, USA, Mar. 14-19, 2010.

  13. Wichern, G., Yamada, M., Thornburg, H., Sugiyama, M., & Spanias, A.
    Automatic Audio Tagging using Covariate Shift Adaptation.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2010), pp.253-256, Dallas, Texas, USA, Mar. 14-19, 2010.

  14. Kondo, K., Yamada, M., & Kenmochi, H.
    A Semi-blind Source Separation Method with A Less Amount of Computation Suitable for Tiny DSP Modules.
    In Proceedings of Interspeech, pp.1339–1342, Brighton, U.K, Sept. 6-10, 2009.

  15. Yamada, M., Sugiyama, M., & Matsui, T.,
    Covariate Shift Adaptation for Semi-supervised Speaker Identification.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2009), pp.1661-1664, Taipei, Taiwan, Apr. 19-24, 2009.

  16. Yamada, M. & Azimi-Sadjadi, M. R..
    Kernel Wiener Filter with Distance Constraint.
    In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2006), Toulouse, France, May 14-19, 2006.

  17. Yamada, M. & Azimi-Sadjadi, M. R..
    Nonlinear signal estimation using kernel Wiener filter in Canonical Correlation Analysis Framework.
    International Conference on Computational Intelligence for Modelling Control and Automation - CIMCA’2005, 28 - 30 November 2005, Vienna - Austria.

  18. Yamada, M. Cartmill, J., & Azimi-Sadjadi, M. R..
    Buried Underwater Target Classification Using the New BOSS and Canonical Coordinate Decomposition Feature Extraction.
    MTS/IEEE Oceans Conference, 2005

  19. Yamada, M. & Azimi-Sadjadi, M. R..
    Kernel Wiener Filter using Canonical Correlation Analysis Framework.
    IEEE Workshop on Statistical Signal Processing 2005 (SSP2005), Bordeaux, France, July 17-20, 2005.

  20. Yamada, M., Pezeshki, A., & Azimi-Sadjadi, M. R..
    Relation between KCCA and KFDA.
    International Joint Conference on Neural Networks (IJCNN2005), Montreal Canada, July 31 to August 4, 2005

Journal Articles

  1. Sugiyama, M. & Yamada, M.
    On kernel parameter selection in Hilbert-Schmidt independence criterion.
    IEICE Transactions on Information and Systems, to appear.

  2. Yamada, M., Sugiyama, M., Wichern, G., & Simm, J.
    Improving the accuracy of least-squares probabilistic classifiers.
    IEICE Transactions on Information and Systems, vol.E94-D, no.6, pp.1337-1340.

  3. Sugiyama, M., Yamada, M., von Bunau, P., Suzuki, T., Kanamori, T., & Kawanabe, M.
    Direct Density-ratio Estimation with Dimensionality Reduction via Least-squares Hetero-distributional Subspace Search.
    Neural Networks, vol.24, no.2, pp183-198, 2011.

  4. Yamada, M., Sugiyama, M., Wichern, G., & Simm, J.
    Direct importance estimation with a mixture of probabilistic principal component analyzers.
    IEICE Transactions on Information and Systems, vol.E93-D, no.10, pp.2846-2849, 2010.

  5. Yamada, M., Sugiyama, M., & Matsui, T.
    Semi-supervised speaker identification under covariate shift.
    Signal Processing, vol.90, no.8, pp.2353-2361, 2010.

  6. Yamada, M. & Sugiyama, M.
    Direct importance estimation with Gaussian mixture models.
    IEICE Transactions on Information and Systems, vol.E92-D, no.10, pp.2159-2162, 2009.

Technical Reports

  1. Yamada, M., Niu, G., Takagi, J. & Sugiyama, M.
    Sufficient Component Analysis for Supervised Dimension Reduction.
    arXiv:1103.4998. [paper]

  2. Yamada, M., Sugiyama, M., & Sese, J.
    Least-Squares Independence Regression for Non-Linear Causal Inference under Non-Gaussian Noise.
    arXiv:1103.5537. [paper]

  3. Takagi, J., Ohishi, Y., Kimura, A., Sugiyama, M., Yamada, M., & Kameoka, H.
    Automatic audio tagging and retrieval based on semi-supervised canonical density estimation.
    IEICE Technical Report, PRMU2010-126, pp.1-6, Yamaguchi, Japan, Dec. 9-10, 2010.

  4. Yamada, M. & Sugiyama, M.
    Cross-domain object matching via maximization of squared-loss mutual information.
    IEICE Technical Report, IBISML2010-61, pp.13-18, Tokyo, Japan, Nov. 4-6, 2010.

  5. Yamada, M., Sugiyama, M., Wichern, G. & Simm, J.
    Improving the Accuracy of Least-Squares Probabilistic Classifiers.
    IEICE Technical Report, IBISML2010-32, pp.45-50, Fukuoka, Japan, Sep. 5-6, 2010.

  6. Yamada, M. & Sugiyama, M.
    Dependence minimizing regression with model selection for non-linear causal inference under non-Gaussian noise.
    IEICE Technical Report, IBISML2010-22, pp.145-151, Tokyo, Japan, Jun. 14-15, 2010.

Others

  1. Yamada, M. & Sugiyama, M.
    Dependence minimizing regression with model selection for non-linear causal inference under non-Gaussian noise.
    Presented at the Second Asian Conference on Machine Learning (ACML2010), Tokyo, Japan, Nov. 8-10, 2010.

Thesis

  1. Yamada, M.
    Kernel Methods and Frequency Domain Independent Component Analysis for Robust Speaker Identification.
    Doctor Thesis, Department of Statistical Science, The Graduate University for Advanced Studies, Hayama, Japan, Mar. 2010.