Pubications with Indistry Partners

• NTT
• Nikon
• Toray Engineering
• NEC Soft
• IBM
• Canon
• YAMAHA
• Microsoft

NTT

• Hachiya, H., Sugiyama, M. & Ueda, N.
  Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition.
  Neurocomputing, vol.80, pp.93-101, 2012.
  [ paper ]
  
  
• 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.
  [ paper ]
  
  
• Kimura, A., Sugiyama, M., Kameoka, H., & Sakano, H.
  Generalized multivariate analysis wih extended pairwise expression.
  In Proceedings of Meeting on Image Recognition and Understanding 2011 (MIRU2011), pp.10-17, Ishikawa, Japan, Jul. 20-22, 2011.
  
  
• Hachiya, H., Sugiyama, M. & Ueda, N.
  Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition.
  In Proceedings of The 5th International Workshop on Data-Mining and Statistical Science (DMSS2011), Osaka, Japan, Mar. 29-30, 2011.
  
  
• Hachiya, H., Sugiyama, M. & Ueda, N.
  Coping with new user problems: Transfer learning in accelerometer-based human activity recognition.
  NIPS 2010 Workshop on Transfer Learning by Learning Rich Generative Models, Whistler, British Columbia, Canada, Dec. 11, 2010.
  
  
• Kimura, A., Kameoka, H., Sugiyama, M., Maeda, E., Sakano, H., & Ishiguro, K.
  SemiCCA: Efficient semi-supervised learning of canonical correlations.
  In Proceedings of 20th International Conference on Pattern Recognition (ICPR2010), pp.2933-2936, Istanbul, Turkey, Aug. 23-26, 2010.
  [ paper ]
  
  
• 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.
  
  
• Takagi, J., Ohishi, Y., Kimura, A., Sugiyama, M., & Kameoka, H.
  Automatic audio tagging and retrieval based on semi-supervised canonical density estimation.
  Presented at 2010 Workshop on Information-Based Induction Sciences (IBIS2010), Tokyo, Japan, Nov. 4-6, 2010.
  
  
• Kimura, A., Nakano, T., Sugiyama, M., Kameoka, H., Maeda, E., & Sakano, H.
  SSCDE: Semi-supervised canonical density estimation for automatic image annotation retrieval.
  In Proceedings of Meeting on Image Recognition and Understanding 2010 (MIRU2010), pp.1396-1403, Hokkaido, Japan, Jul. 27-29, 2010.
  (This paper was selected for Best Interactive Session Award)
  
  
• Kimura, A., Kameoka, H., Sugiyama, M., Maeda, E., Sakano, H., & Ishiguro, K.
  SemiCCA: Efficient semi-supervised learning of canonical correlations.
  Presented at 2009 Workshop on Information-Based Induction Sciences (IBIS2009), Fukuoka, Japan, Oct. 19-21, 2009.
  
  

Nikon

• Nakajima, S., Sugiyama, M., Babacan, D., & Tomioka, R.
  Global analytic solution of fully-observed variational Bayesian matrix factorization.
  Journal of Machine Learning Research, to appear.
  [ paper ]
  
  
• Nakajima, S., Tomioka, R., Sugiyama, M., & Babacan, D.
  Perfect dimensionality recovery by variational Bayesian PCA.
  In X. XXX, Y. YYY, and Z. ZZZ (Eds.), Advances in Neural Information Processing Systems 25, pp.xxx-xxx, 2012.
  (Presented at Neural Information Processing Systems (NIPS2012), Lake Tahoe, Nevada, USA, Dec. 3-6, 2012)
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  Sparse additive matrix factorization for robust PCA and its generalization.
  In S. C. H. Hoi and W. Buntine (Eds.), Proceedings of the Fourth Asian Conference on Machine Learning (ACML2012), JMLR Workshop and Conference Proceedings, vol.25, pp.xxx-xxx, Singapore, Nov. 4-6, 2012.
  [ paper ]
  
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  Sparse additive matrix factorization for robust PCA and its generalization.
  In S. C. H. Hoi and W. Buntine (Eds.), Proceedings of the Fourth Asian Conference on Machine Learning (ACML2012), JMLR Workshop and Conference Proceedings, vol.25, pp.xxx-xxx, Singapore, Nov. 4-6, 2012.
  [ paper ]
  
  
• Nakajima, S. & Sugiyama, M.
  Theoretical Analysis of Bayesian Matrix Factorization.
  Journal of Machine Learning Research, vol.12 (Sep.), pp.2583-2648, 2011.
  [ paper ]
  
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  Global solution of fully-observed variational Bayesian matrix factorization is column-wise independent.
  In J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F. Pereira, and K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 24, pp.xxx-xxx, 2011.
  (Presented at Neural Information Processing Systems (NIPS2011), Granada, Spain, Dec. 13-15, 2011)
  [ paper ]
  
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  On Bayesian PCA: Automatic dimensionality selection and analytic solution.
  In L. Getoor and T. Scheffer (Eds.), Proceedings of 28th International Conference on Machine Learning (ICML2011), pp.497-504, Bellevue, Washington, USA, Jun. 28-Jul. 2, 2011.
  [ paper ]
  
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  Global solution of variational Bayesian matrix factorization under matrix-wise independence.
  IEICE Technical Report, IBISML2011-17, pp.1-8, Hokkaido, Japan, Sep. 5-6, 2011.
  
  
• Nakajima, S., Sugiyama, M., & Babacan, D.
  On automatic dimensionality selection in probabilistic PCA.
  IEICE Technical Report, IBISML2010-123, pp.131-138, Osaka, Japan, Mar. 28-29, 2011.
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  Machine Learning, vol.78, no.1-2, pp.35-61, 2010.
  [ paper ]
  
  
• Nakajima, S. & Sugiyama, M.
  On non-identifiability of Bayesian matrix factorization models.
  In T. Joachims and J. Fürnkranz (Eds.), Proceedings of 27th International Conference on Machine Learning (ICML2010), pp.815-822, Haifa, Israel, Jun. 21-25, 2010.
  [ paper ]
  
  
• Nakajima, S. & Sugiyama, M.
  Model-induced regularization.
  Presented at the Second Asian Conference on Machine Learning (ACML2010), Tokyo, Japan, Nov. 8-10, 2010.
  
  
• Nakajima, S., Sugiyama, M., & Tomioka, R.
  Global analytic solution for variational Bayesian matrix factorization and its model-induced regularization.
  IEICE Technical Report, IBISML2010-99, pp.291-302, 2010.
  (Presented at 2010 Workshop on Information-Based Induction Sciences (IBIS2010), Tokyo, Japan, Nov. 4-6, 2010)
  
  
• Sugiyama, M. & Nakajima, S.
  Pool-based active learning in approximate linear regression.
  Machine Learning, vol.75, no.3, pp.249-274, 2009.
  [ paper ]
  
  
• Nakajima, S. & Sugiyama,M.
  Analysis of variational Bayesian matrix factorization.
  In T. Theeramunkong, B. Kijsirikul, N. Cercone, and T.-B. Ho (Eds.), Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, vol.5476, pp.314-326, Berlin, Springer, 2009.
  (Presented at the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2009), Bangkok, Thailand, Apr. 27-30, 2009)
  [ paper ]
  
  
• Sugiyama, M., Suzuki, T., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Direct importance estimation for covariate shift adaptation.
  Annals of the Institute of Statistical Mathematics, vol.60, no.4, pp.699-746, 2008.
  [ paper ]
  
  
• Sugiyama, M. & Nakajima, S.
  Pool-based agnostic experiment design in linear regression.
  In W. Daelemans, B. Goethals, and K. Morik (Eds.), Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science, vol.5212, pp.406-422, Berlin, Springer, 2008.
  (Presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD2008), Antwerp, Belgium, Sep. 15-19, 2008)
  [ paper, slides ]
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  In T. Washio, E. Suzuki, K. M. Ting, and A. Inokuchi (Eds.), Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, vol.5012, pp.333-344, Berlin, Springer, 2008.
  (Presented at the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2008), Osaka, Japan, May 20-24, 2008)
  [ paper, slides ]
  
  
• Sugiyama, M., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Direct importance estimation with model selection and its application to covariate shift adaptation.
  In J. C. Platt, D. Koller, Y. Singer, and S. Roweis (Eds.), Advances in Neural Information Processing Systems 20, pp.1433-1440, Cambridge, MA, MIT Press, 2008.
  (Presented at Neural Information Processing Systems (NIPS2007), Vancouver, British Columbia, Canada, Dec. 3-8, 2007)
  [ paper, poster ]
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  In Proceedings of 2007 Workshop on Information-Based Induction Sciences (IBIS2007), pp.1-6, Yokohama, Japan, Nov. 5-7, 2007.
  
  
• Sugiyama, M., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Kullback-Leibler importance estimation procedure for covariate shift adaptation.
  In Proceedings of the International Workshop on Data-Mining and Statistical Sciences (DMSS2007) , pp.31-49, Tokyo, Japan, Oct. 5-6, 2007.
  
  

Toray Engineering

• Mori, S., Sugiyama, M., Ogawa, H., Kitagawa, K., & Irie, K.
  Automatic parameter optimization of the local model fitting method for single-shot surface profiling.
  Applied Optics, vol.50, no.21, pp.3773-3780, 2011.
  [ paper ]
  
  
• Mori, S., Sugiyama, M., Ogawa, H., Kitagawa, K., & Irie, K.
  Automatic parameter optimization of the local model fitting method for single-shot surface profiling.
  In Proceedings of the Japan Society for Precision Engineering 2011 Spring Meeting, pp.1031-1032, Tokyo, Japan, Mar. 14-16, 2011.
  
  
• Kurihara, N., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  Iteratively-reweighted local model fitting method for adaptive and accurate single-shot surface profiling.
  Applied Optics, vol.49, no.22, pp.4270-4277, 2010.
  [ paper ]
  
  
• Kurihara, N., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  One-shot surface profiling by weighted local model fitting.
  In Proceedings of Dynamic Image Processing for Real Application (DIA2010), pp.249-254, Yamanashi, Japan, Mar. 4-5, 2010.
  
  
• Naito, T., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.,
  Single-shot interferometry of film-covered objects.
  Journal of the Japan Society for Precision Engineering, vol.75, no.11, pp.1315-1322, 2009.
  [ paper in Japanese ]
  
  
• Yokota, T., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  The interpolated local model fitting method for accurate and fast single-shot surface profiling.
  Applied Optics, vol.48, no.18, pp.3497-3508, 2009.
  [ paper (revised version) ]
  
  
• Ogawa, H., Nakanowatari, A., Kitagawa, K., Sugiyama, M., & Naito, T.
  Simultaneous measurement of film thickness and surface profile of film-covered objects by monochromatic light interferometry.
  Transactions of the Society of Instrument and Control Engineers, vol.45, no.2, pp.73-82, 2009.
  [ paper in Japanese ]
  
  
• Kitagawa, K., Sugiyama, M., Matsuzaka, T., Ogawa, H., & Suzuki, K.,
  Two-wavelength single-shot interferometry.
  Journal of the Japan Society for Precision Engineering, vol.75, no.2, pp.273-277, 2009.
  [ paper in Japanese ]
  
  
• Yokota, T., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  Error analysis of local model fitting method in single-shot surface profiling.
  In Proceedings of the Japan Society for Precision Engineering, 2009 Spring Meeting, no.C02, pp.167-168, Tokyo, Japan, Mar. 11-13, 2009
  
  
• Kitagawa, K., Sugiyama, M., Matsuzaka, T., Ogawa, H., & Suzuki, K.
  Two-wavelength single-shot interferometry.
  Image Lab, vol.19, no.10, pp.37-43, 2008.
  [ paper in Japanese ]
  
  
• Kitagawa, K., Sugiyama, M., Matsuzaka, T., Ogawa, H., & Suzuki, K.
  Two-wavelength single-shot interferometry.
  Eizojoho Industrial, vol.40, no.2, pp.51-58, 2008.
  
  
• Naito, T., Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  Single-shot interferometry of film-covered objects: local model fitting for simultaneous measurement of film thickness and surface profile of film-covered objects.
  In Proceedings of The Japan Society for Precision Engineering 2008 Autumn Semestrial Conference, no.C33, pp.183-184, Sendai, Japan, Sep. 17-19, 2008.
  
  
• Suzuki, K., Ogawa, H., Kitagawa, K., & Sugiyama, M.
  Two-wavelength single-shot interferometry for precise surface profiling.
  In Proceedings of Optical Measurement Symposium 2008, pp.35-38, Yokohama, Japan, Jun. 11, 2008.
  
  
• Ogawa, H., Shimoyama, K., Fukunaga, M., Kitagawa, K., & Sugiyama, M.
  Simultaneous measurement of film thickness and surface profile of film-covered objects by using white-light interferometry.
  Transactions of the Society of Instrument and Control Engineers, vol.43, no.2, pp.71-77, 2007.
  [ paper in Japanese ]
  
  
• Kitagawa, K., Sugiyama, M., Matsuzaka, T., Ogawa, H., & Suzuki, K.
  Two-wavelength single-shot interferometry.
  In Proceedings of Vision Engineering Workshop 2007 (ViEW2007), pp.189-194, Yokohama, Japan, Dec. 6-7, 2007.
  (This paper was selected for Odawara Award 2nd Prize)
  
  
• Kitagawa, K., Sugiyama, M., Matsuzaka, T., Ogawa, H., & Suzuki, K.
  Two-wavelength single-shot interferometry.
  In Proceedings of the Society of Instrument and Control Engineers Annual Conference (SICE2007), pp.724-728, Takamatsu, Japan, Sep. 17-20, 2007.
  
  
• Sugiyama, M., Matsuzaka, T., Ogawa, H., Kitagawa, K., & Suzuki, K.
  One-shot profiling of sharp bumpy surfaces.
  In Proceedings of the Japan Society for Precision Engineering 2007 Spring Meeting, no.G07, pp.586-587, Tokyo, Japan, Mar. 20-22, 2007.
  
  
• Sugiyama, M., Ogawa, H., Kitagawa, K., & Suzuki, K.
  Single-shot surface profiling by local model fitting.
  Applied Optics, vol.45, no.31, pp.7999-8005, 2006.
  [ paper ]
  
  
• Ogawa, H., Nakanowatari, A., Kitagawa, K., & Sugiyama, M.
  3-D profiling of film-covered objects using phase-shifting interferometry.
  In Proceedings of the 2004 Autumn Meeting of the Japan Society for Precision Engineering, pp.1125-1126, Shimane, Japan, Sep. 15-17, 2004. (in Japanese)
  
  

NEC Soft

• Ueki, K., Sugiyama, M., & Ihara, Y.
  Lighting condition adaptation for perceived age estimation.
  IEICE Transactions on Information and Systems, vol.E94-D, no.2, pp.392-395, 2011.
  [ paper ]
  
  
• Ueki, K., Ihara, Y., & Sugiyama, M.
  Perceived age estimation from face images.
  In G. Chetty and J. Yang (Eds.), Advanced Biometric Technologies, Chapter 16, pp.325-342, InTech, Rijeka, Croatia, 2011.
  [ paper ]
  
  
• Ueki, K., Sugiyama, M., Ihara, Y., & Fujita, M.
  Multi-race age estimation based on the combination of multiple classifiers.
  In Proceedings of the First Asian Conference on Pattern Recognition (ACPR2011), pp.633-637, Beijing, China, Nov. 28-30, 2011.
  [ paper ]
  
  
• Ihara, Y., Sugiyama, M., Ueki, K., & Fujita, M.
  Multi-race age classification by weighted combination of multiple classifiers.
  Dynamic Image Processing for Real Application (DIA2010), pp.317-322, Tokushima, Japan, Mar. 3-4, 2011.
  
  
• Ueki, K., Sugiyama, M., & Ihara, Y.
  A semi-supervised approach to perceived age prediction from face images.
  IEICE Transactions on Information and Systems, vol.E93-D, no.10, pp.2875-2878, 2010.
  [ paper ]
  
  
• Ueki, K., Sugiyama, M., & Ihara, Y.
  Perceived age estimation under lighting condition change by covariate shift adaptation.
  In Proceedings of 20th International Conference on Pattern Recognition (ICPR2010), pp.3400-3403, Istanbul, Turkey, Aug. 23-26, 2010.
  [ paper ]
  
  
• Ueki, K., Sugiyama, M., & Ihara, Y.
  Semi-supervised estimation of perceived age from face images.
  In Proceedings of International Conference on Computer Vision Theory and Applications (VISAPP2010), pp.319-324, Angers, France, May 17-21, 2010.
  [ paper ]
  
  
• Ihara, Y., Sugiyama, M., & Ueki, K.
  Age estimation using covariate shift adaptation.
  In Proceedings of Vision Engineering Workshop 2009 (ViEW2009), pp.325-330, Yokohama, Japan, Dec. 3-4, 2009.
  
  
• Ueki, K., Sugiyama, M., & Ihara, Y.
  Active sample selection and weighted semi-supervised regression for perceived age estimation.
  In Proceedings of Meeting on Image Recognition and Understanding 2009 (MIRU2009), pp.260-265, Shimane, Japan, Jul. 20-22, 2009.
  
  
• Ueki, K., Sugiyama, M., & Ihara, Y.
  Perceived age estimation using weighted regression.
  In Proceedings of Symposium on Sensing via Image Information (SSII09), no.IS4-23 (CD-ROM), Yokohama, Japan, Jun. 10-12, 2009.
  
  

IBM

• Hido, S., Tsuboi, Y., Kashima, H., Sugiyama, M., & Kanamori, T.
  Statistical outlier detection using direct density ratio estimation.
  Knowledge and Information Systems, vol.26, no.2, pp.309-336, 2011.
  [ paper ]
  
  
• Ide, T. & Sugiyama, M.
  Trajectory regression on road networks.
  In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI2011), pp.203-208, San Francisco, California, USA, Aug. 7-11, 2011.
  [ paper ]
  
  
• Sugiyama, M., Hachiya, H., Kashima, H., & Morimura, T.
  Least absolute policy iteration---A robust approach to value function approximation.
  IEICE Transactions on Information and Systems, vol.E93-D, no.9, pp.2555-2565, 2010.
  [ paper ]
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  Machine Learning, vol.78, no.1-2, pp.35-61, 2010.
  [ paper ]
  
  
• Morimura, T., Sugiyama, M., Kashima, H., Hachiya, H., & Tanaka, T.
  Parametric return density estimation for reinforcement learning.
  In Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI2010), pp.368-375, Catalina Island, California, USA, Jul. 8-11, 2010.
  [ paper ]
  
  
• Morimura, T., Sugiyama, M., Kashima, H., Hachiya, H., & Tanaka, T.
  Nonparametric return distribution approximation for reinforcement learning.
  In T. Joachims and J. Fürnkranz (Eds.), Proceedings of 27th International Conference on Machine Learning (ICML2010), pp.799-806, Haifa, Israel, Jun. 21-25, 2010.
  [ paper ]
  
  
• Morimura, T., Sugiyama, M., Kashima, H., Hachiya, H., & Tanaka, T.
  Return density estimation with dynamic programming.
  IEICE Technical Report, IBISML2010-98, pp.283-290, 2010.
  (Presented at 2010 Workshop on Information-Based Induction Sciences (IBIS2010), Tokyo, Japan, Nov. 4-6, 2010)
  
  
• Morimura, T., Sugiyama, M., Kashima, H., Hachiya, H., & Tanaka, T.
  Convergence analysis of dynamic programming for distributional Bellman equation.
  In Proceedings of Electronics, Information and Systems Conference, Electronics, Information and Systems Society, Institute of Electrical Engineers of Japan, pp.178-183, Kumamoto, Japan, Sep. 2-3, 2010.
  
  
• Sugiyama, M., Kanamori, T., Suzuki, T., Hido, S., Sese, J., Takeuchi, I., & Wang, L.
  A density-ratio framework for statistical data processing.
  IPSJ Transactions on Computer Vision and Applications, vol.1, pp.183-208, 2009.
  [ paper ]
  
  
• Kanamori, T., Hido, S., & Sugiyama, M.
  A least-squares approach to direct importance estimation.
  Journal of Machine Learning Research, vol.10 (Jul.), pp.1391-1445, 2009.
  [ paper, software (html) ]
  
  
• Kashima, H., Idé, T., Kato, T., & Sugiyama, M.
  Recent advances and trends in large-scale kernel methods.
  IEICE Transactions on Information and Systems, vol.E92-D, no.7, pp.1338-1353, 2009.
  [ paper ]
  
  
• Tsuboi, Y., Kashima, H., Hido, S., Bickel, S., & Sugiyama, M.
  Direct density ratio estimation for large-scale covariate shift adaptation.
  Journal of Information Processing, vol.17, pp.138-155, 2009.
  [ paper ]
  
  
• Kato, T., Kashima, H., & Sugiyama, M.
  Robust label propagation on multiple networks.
  IEEE Transactions on Neural Networks, vol.20, no.1, pp.35-44, 2009.
  [ paper ]
  
  
• Sugiyama, M., Hachiya, H., Kashima, H., & Morimura, T.
  Least absolute policy iteration for robust value function approximation.
  In A. Bicchi (Ed.), Proceedings of 2009 IEEE International Conference on Robotics and Automation (ICRA2009), pp.2904-2909, Kobe, Japan, May 12-17, 2009.
  [ paper, demo (mp4) ]
  
  
• Kashima, H., Kato, T., Yamanishi, Y., Sugiyama, M., & Tsuda, K.
  Link propagation: A fast semi-supervised learning algorithm for link prediction.
  In H. Park, S. Parthasarathy, H. Liu, H., and Z. Obradovic (Eds.), Proceedings of 2009 SIAM International Conference on Data Mining (SDM2009), pp.1099-1110, Sparks, Nevada, USA, Apr. 30-May 2, 2009.
  [ paper ]
  
  
• Morimura, T., Sugiyama, M., Kashima, H., Hachiya, H., & Tanaka, T.
  Return distribution estimation for risk-sensitive reinforcement learning.
  Presented at 2009 Workshop on Information-Based Induction Sciences (IBIS2009), Fukuoka, Japan, Oct. 19-21, 2009.
  
  
• Sugiyama, M., Kanamori, T., Suzuki, T., Hido, S., Sese, J., Takeuchi, I., & Wang, L.
  Methods and applications of density ratio estimation,
  In Proceedings of Acoustical Society of Japan 2009 Spring Meeting, no.2-5-12, pp.73-76, Tokyo, Japan, Mar. 17-19, 2009.
  
  
• Kashima, H., Kato, T., Yamanishi, Y., Sugiyama, M., & Tsuda, K.
  Link propagation: A fast semi-supervised learning algorithm for link prediction.
  In Proceedings of the Japanese Society for Artificial Intelligence, 73rd Meeting of Special Interest Group on Fundamental Problem in Artificial Intelligence, pp.19-24, Tokyo, Japan, Mar. 13-14, 2009.
  
  
• Sugiyama, M., Suzuki, T., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Direct importance estimation for covariate shift adaptation.
  Annals of the Institute of Statistical Mathematics, vol.60, no.4, pp.699-746, 2008.
  [ paper ]
  
  
• Hido, S., Tsuboi, Y., Kashima, H., Sugiyama, M., & Kanamori, T.
  Inlier-based outlier detection via direct density ratio estimation.
  In F. Giannotti, D. Gunopulos, F. Turini, C. Zaniolo , N. Ramakrishnan, and X. Wu (Eds.), Proceedings of IEEE International Conference on Data Mining (ICDM2008), pp.223-232, Pisa, Italy, Dec. 15-19, 2008.
  [ paper, slides ]
  
  
• Kanamori, T., Hido, S., & Sugiyama, M.
  Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection.
  In D. Koller, D. Schuurmans, Y. Bengio, and L. Botton (Eds.), Advances in Neural Information Processing Systems 21, pp.809-816, Cambridge, MA, MIT Press, 2009.
  (Presented at Neural Information Processing Systems (NIPS2008), Vancouver, British Columbia, Canada, Dec. 8-13, 2008)
  [ paper, poster ]
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  In T. Washio, E. Suzuki, K. M. Ting, and A. Inokuchi (Eds.), Advances in Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, vol.5012, pp.333-344, Berlin, Springer, 2008.
  (Presented at the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2008), Osaka, Japan, May 20-24, 2008)
  [ paper, slides ]
  
  
• Kato, T., Kashima, H., & Sugiyama, M.
  Integration of multiple networks for robust label propagation.
  In M. J. Zaki, K. Wang, C. Apte, and H. Park (Eds.), Proceedings of the Eighth SIAM International Conference on Data Mining (SDM2008), pp.716-726, Atlanta, Georgia, USA, Apr. 24-26, 2008.
  [ paper ]
  
  
• Tsuboi, Y., Kashima, H., Hido, S., Bickel, S., & Sugiyama, M.
  Direct density ratio estimation for large-scale covariate shift adaptation.
  In M. J. Zaki, K. Wang, C. Apte, and H. Park (Eds.), Proceedings of the Eighth SIAM International Conference on Data Mining (SDM2008), pp.443-454, Atlanta, Georgia, USA, Apr. 24-26, 2008.
  [ paper ]
  
  
• Kato, T., Kashima, H., & Sugiyama, M.
  Using product-of-Student-t for label propagation on multiple networks.
  In Proceedings of The Third International Workshop on Data-Mining and Statistical Science (DMSS2008), pp.20-23, Tokyo, Japan, Sep. 25-26, 2008.
  
  
• Kato, T., Kashima, H., & Sugiyama, M.
  Protein function prediction by integration of heterogenous biological networks.
  In Proceedings of Information Processing Society of Japan (IPSJ), Special Interest Group on Bioinformatics and Genomics (SIG BIO), vol.2008, no.86, pp.47-50, Sapporo, Japan, Sep. 18-19, 2008.
  
  
• Kanamori, T., Hido, S., & Sugiyama, M.
  Learning and density ratio estimation under covariate shift.
  The 2008 Japanese Joint Statistical Meeting, p.196, Yokohama, Japan, Sep. 7-10, 2008.
  
  
• Sugiyama, M., Kanamori, T., Suzuki, T., Hido, S., Sese, J., Takeuchi, I., & Wang, L.
  Direct importance estimation---A new versatile tool for statistical pattern recognition.
  In Proceedings of Meeting on Image Recognition and Understanding 2008 (MIRU2008), pp.29-36, Nagano, Japan, Jul. 29-31, 2008.
  (This paper was selected for Best Paper Runner-up Award)
  
  
• Sugiyama, M., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Direct importance estimation with model selection and its application to covariate shift adaptation.
  In J. C. Platt, D. Koller, Y. Singer, and S. Roweis (Eds.), Advances in Neural Information Processing Systems 20, pp.1433-1440, Cambridge, MA, MIT Press, 2008.
  (Presented at Neural Information Processing Systems (NIPS2007), Vancouver, British Columbia, Canada, Dec. 3-8, 2007)
  [ paper, poster ]
  
  
• Kato, T., Kashima, H., Sugiyama, M., & Asai, K.
  Multi-task learning via conic programming.
  In J. C. Platt, D. Koller, Y. Singer, and S. Roweis (Eds.), Advances in Neural Information Processing Systems 20, pp.737-744, Cambridge, MA, MIT Press, 2008.
  (Presented at Neural Information Processing Systems (NIPS2007), Vancouver, British Columbia, Canada, Dec. 3-8, 2007)
  [ paper ]
  
  
• Sugiyama, M., Idé, T., Nakajima, S., & Sese, J.
  Semi-supervised local Fisher discriminant analysis for dimensionality reduction.
  In Proceedings of 2007 Workshop on Information-Based Induction Sciences (IBIS2007), pp.1-6, Yokohama, Japan, Nov. 5-7, 2007.
  
  
• Hido, S., Tsuboi, Y., Kashima, H., & Sugiyama, M.
  Novelty detection by density ratio estimation.
  In Proceedings of 2007 Workshop on Information-Based Induction Sciences (IBIS2007), pp.197-204, Yokohama, Japan, Nov. 5-7, 2007.
  
  
• Kato, T., Kashima, H., Sugiyama, M., & Asai, K.
  Probabilistic label propagation on multiple networks.
  In Proceedings of 2007 Workshop on Information-Based Induction Sciences (IBIS2007), pp.43-48, Yokohama, Japan, Nov. 5-7, 2007.
  
  
• Sugiyama, M., Nakajima, S., Kashima, H., von Bünau, P., & Kawanabe, M.
  Kullback-Leibler importance estimation procedure for covariate shift adaptation.
  In Proceedings of the International Workshop on Data-Mining and Statistical Sciences (DMSS2007) , pp.31-49, Tokyo, Japan, Oct. 5-6, 2007.
  
  

Canon

• Matsugu, M., Yamanaka, M., & Sugiyama, M.
  Detection of activities and events without explicit categorization.
  In Proceedings of Proceedings of the 3rd International Workshop on Video Event Categorization, Tagging and Retrieval for Real-World Applications (VECTaR2011), pp.1532-1539, Barcelona, Spain, Nov. 13, 2011.
  [ paper ]
  
  
• Yamanaka, M., Matsugu, M. & Sugiyama, M.
  Automatic detection of regions of interest based on density ratio estimation.
  In Proceedings of 2011 Annual Conference of I.E.E. of Japan, Industry Applications Society,, no.2-S9-4, pp.143-149, Okinawa, Japan, Sep. 6-8, 2011.
  
  
• Yamanaka, M., Matsugu, M. & Sugiyama, M.
  Automatic detection of regions of interest using multiple visual saliency measures based on density ratio estimation.
  In Proceedings of Vision Engineering Workshop 2010 (ViEW2010), pp.7-8, Yokohama, Japan, Dec. 9-10, 2010.
  
  
• Yamanaka, M., Matsugu, M. & Sugiyama, M.
  Application of density ratio estimation to region-of-interest detection in images.
  In Proceedings of Meeting on Image Recognition and Understanding 2010 (MIRU2010), pp.67-74, Hokkaido, Japan, Jul. 27-29, 2010.
  
  
• Takimoto, M., Matsugu, M., & Sugiyama, M.
  Visual inspection of precision instruments by least-squares outlier detection.
  In Proceedings of The Fourth International Workshop on Data-Mining and Statistical Science (DMSS2009), pp.22-26, Kyoto, Japan, Jul. 7-8, 2009.
  
  

YAMAHA

• Yamada, M., Wichern, G., Sugiyama, M., & Kondo, K.
  Semi-blind source separation under ambient noise condition change.
  In Proceedings of Acoustical Society of Japan 2009 Autumn Meeting, pp.751-754, Fukushima, Japan, Sep. 15-17, 2009.
  
  
• Yamada, M., Sugiyama, M., & Matsui, T.
  Covariate shift adaptation for speaker identification.
  In Proceedings of Acoustical Society of Japan 2009 Spring Meeting, no.2-5-13, pp.77-78, Tokyo, Japan, Mar. 17-19, 2009.
  
  

Microsoft

• Quiñonero-Candela, J., Sugiyama, M., Schwaighofer, A., & Lawrence, N. D. (Eds.),
  Dataset Shift in Machine Learning,
  MIT Press, Cambridge, MA, USA, 2009.