論文

• Sugiyama, M., Du Plessis M.C., & Yamada, M.. Learning under non-stationarity:Covariate shift and class-balance change, WIREs Computational Statistics, 2013.
• Yamada, M., Jitkrittum, W., Sigal, L., Xing, E.P., &Sugiyama, M.. High-dimensional feature selectionby feature-wise kernelized lasso, Neural Computational Statistics, 2013.
• Yamada, M., Suzuki, T., Kanamori, T., Hachiya, H., Sugiyama, M.. Relatiive density-ratio estimationfor robust distribution comparision, Neural Computation, vol. 25, no. 5, pp. 1324-1370, 2013.
• Liu, S., Yamada, M., Collier, N., Sugiyama, M. Change-point detection in time-series data b;y relative density-ratio estimastion, Neural Networks, vol. 43, pp. 72-83, 2013.
• Sugiyama, M., Liu, S., Du Plessis, M.C., Yamanaka, M., Yamada, M., Suzuki, T., & Kanamori, T.. Direct divergence approximationbetween probability distributions and its applications inmachine learning, Journal of Computing Science and Engineering, vol. 7, no. 2, pp. 99-111, 2013.
• Sugiyama, M., Gang, N., Yamada, M., Kimura, M., & Hachiya, H.. Information-maximization clustering based on squared-loss mutual information, Neural Computation, 2013.
• Yamada, M., Wichern, G., Kondo, K., Sugiyama, M., Sawada, H.. Noise adaptive optimization of matrix initialization for frequency-domain independent component analysis, Digital Signal Processing, vol. 13, no. 1, pp. 1-8,2013, Aug. 2012.
• Sugiyama, M., Yamada, M.. On kernel parameter selection in Hilbert-Schmidt independence criterion., IEICE, IEICE Transactions on Information and Systems,, vol. 95-D, no. 10, pp. 2564-2567, 2012.

国際会議発表 (査読有り)

• Sugiyama, M., Yamada, M., Kimura, M., Hachiya, H.. Information-maximization clustering: Analytic solution and model selection., IEICE Technical Report, IBISML2010-114, pp. 69-76, Feb. 2012.
• Sugiyama, M., Yamada, M., von Bünau, P., Suzuki, T., Kanamori, T., Kawanabe, M.. Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search., Neural Networks, vol. 26, no. 2, pp. 309－336, 2011.
• Yamada, M., Sugiyama, M.. Dependence minimizing regression with model selection for non-linear causal inference under non-Gaussian noise., the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), pp. 643-648, July 2010.
• Yamada, M., Sugiyama, M.. Dependence minimizing regression with model selection for non-linear causal inference under non-Gaussian noise., IBISML2010-22, IEICE Technical Report, IBISML2010-22, pp. 145-151, June 2010.
• Yamada, M., Sugiyama, M., Wichern, G.. Direct importance estimation with probabilistic principal component analyzers., IEEEInternational Conference on Acoustics, Speech, and Signal Processing(ICASSP2010), In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2010), pp. 1962-1965, Mar. 2010.
• Gordon, W., Yamada, M., Harvey, T., Sugiyama, M., Andreas, S.. Automatic audio tagging using covariate shift adaptation., Acoustical Society of Japan 2010 Spring Meeting,, In Proceeding of Acoustical Society of Japan 2010 Spring Meening, no. 2-8-19, pp. 989-990, Mar. 2010.
• Wichern, G., Yamada, M., Thornburg, H., Sugiyama, M., Spanias, A.. Automatic audio tagging using covariate shift adaptation., IEEE International Conference on Acoustics, Speech, and Signal Processing(ICAASP2010), In Proceeding of IEEEInternational Conference on Acoustics, Speech, and Signal Processing(ICASSP2010), pp. 253-256, Mar. 2010.

国内会議発表 (査読有り)

• 高木 潤, 杉山 将, 木村 昭悟, 八谷 大岳, 大石 康智, 山田 誠.. 簡易半教師付確率的分類器を用いた自動メディアアノテーション, 画像の認識・理解シンポジウム2012 (MIRU2012), 画像の認識・理解シンポジウム2012 (MIRU2012)論文集, Aug. 2012.
• Yamada, M., Sugiyama, M.. Cross-domain object matching via maximization of squared-loss mutual information, 2010 Workshop on Information-Based Induction Sciences (IBIS2010), IEICE Technical Report, IBISML2010-61, pp. 13-18, Nov. 2010.

国際会議発表 (査読なし・不明)

• Niu, G., Dai, B., Yamada, M., Sugiyama, M.. Information-theoretic semi-supervised metric learing via entropy regularization., 29th International Conference on Machine Learning(ICML2012), Proceedings of 29th International Conference on Machine Learning(ACML2012), J.Langford,J.Pineau(EDS.), pp. 89-96, Aug. 2012.
• Yamada, M., Sugiyama, M.. Direct density-ratio estimation with dimensionality reduction via hetero-distributional subspace analysis., the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI2011),, the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI2011),, pp. 549-554, Feb. 2012.
• Yamada, M., Niu, G., Takagi, J., Sugiyama, M.. Computationally efficient sufficient dimension reduction via squared-loss mutual information., the Third Asian Conference on Machine Learning (ACML2011), JMLR Workshop and Conference Proceedings, the Third Asian Conference on Machine Learning (ACML2011), JMLR Workshop and Conference Proceedings, vol. 20, pp. 247-262, Feb. 2012.
• Sugiyama, M., Yamada, M., Kimura, M., Hachiya, H.. On information-maximization clustering: tuning parameter selection and analytic solution., 28th International Conference on Machine Learning (ICML2011), 28th International Conference on Machine Learning (ICML2011), Feb. 2012.
• Liu, S., Yamada, M., Collier, N., Sugiyama, M.. Change-point detection in time-series data by relative density-ratio estimation., 9th International Workshop on Statistical Techniques in Pattern Recognition(SPR2012), Structural, Syntacic ,and statistical Pattern Recognition, Lecture Notes in Compurter Science,Berlin,Sprenger,2012, G.Gimel'farb,E.Hancock,A.Imiya,A.Kuiper,M.Kudo,S.Omachi,T.Windeatt,K.Yamada., vol. 7626, pp. 363-372, 2012.
• Yamada, M., Suzuki, T., Kanamori, T., Hachiya, H., Sugiyama, M.. Relative density-ratio estimation for robust distribution comparison., Neural Information Processing Systems (NIPS2011),, Advances in Neural Information Processing Systems 24, pp. 594-602, Dec. 2011.
• Takagi, J., Ohishi, Y., Kimura, A., Sugiyama, M., Yamada, M., Kameoka, H.. Automatic audio tag classification via semi-supervised canonical density estimation., 28th International Conference on Machine Learning (ICML2011, 28th International Conference on Machine Learning (ICML2011), Bellevue, Washington, USA, pp. 497-504, July 2011.
• Yamada, M., Sugiyama, M.. Cross-domain object matching with model selection, Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS2011),, JMLR Workshop and Conference Proceedings, vol. 15, pp. 807-815, Apr. 2011.

国内会議発表 (査読なし・不明)

• Yamada, M., Jitkrittum, W., Sigal, L., Xing, E.P., Sugiyama, M.. High-dimensional feature selection by feature-wise kernelized lasso, IBIS2012, 2013.
• Takagi, J., Sugiyama, M., Kimura, A., Hachiya, H., Ohishi, Y., & Yamada, M.. Automatic media annotation with simple semi-supervised probabilitic classifiers, Meeting on Image Recognition and Understanding 2012, Aug. 2012.
• Yamada, M., Niu, G., Takagi, J., Sugiyama, M.. Sufficient component analysis for supervised dimension reduction., The 5th International Workshop on Data-Mining and Statistical Science (DMSS2011),, Feb. 2012.
• Liu, S., Yamada, M., Sugiyama, M.. Generalization of matrix factorization for robust PCA., IBISML2011, IEICE Technical Report, IBISML2011-70, pp. 187-198, Feb. 2012.
• Yamada, M., Sugiyama, M.. Multimedia Information processing with mutual information, 2nd Institute of Mathematical Statistics Asia pacific Rim meeting, 2012.
• Yamada, M., Matsugu, M., & Sugiyama, M.. Salient Object detection based on direct density-ratio estimation, IPSJ SIG, IPSJ Transactions on Mathematical Modeling and Its Applications, vol. 2012-MPS-90, no. 5, pp. 1-8, 2012.
• Yamada, M., Suzuki, T., Hachiya, H., Sugiyama, M.. Relative density-ratio estimation for robust distribution comparison., IBISML2011, IEICE Technical Report, IBISML2011-46, pp. 25-32, Nov. 2011.
• Du Plessis, M. C., Yamada, M., Sugiyama, M.. Estimation of squared-loss mutual information from paired and unpaired samples., IBISML2011, IEICE Technical Report, IBISML2011-11, pp. 75-81, June 2011.
• Makoto Yamada, Masashi Sugiyama. Direct density-ratio estimation with dimensionality reduction via hetero-distributional subspace analysis., IBISML2011, IEICE Technical Report, IBISML2011-1, pp. 1-6, June 2011.
• Niu, G., Dai, B., Yamada, M., Sugiyama, M.. SERAPH: Semi-supervised metric learning paradigm with hyper sparsity., IBISML2011, IEICE Technical Report, IBISML2011-8, June 2011.
• 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, IEICE Technical Report, PRMU2010-126, pp. 1-6, Dec. 2010.

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