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Takafumi Kanamori
Takafumi Kanamori
Institute of Science Tokyo
Verified email at comp.isct.ac.jp - Homepage
Title
Cited by
Cited by
Year
Density ratio estimation in machine learning
M Sugiyama, T Suzuki, T Kanamori
Cambridge University Press, 2012
7232012
A least-squares approach to direct importance estimation
T Kanamori, S Hido, M Sugiyama
The Journal of Machine Learning Research 10, 1391-1445, 2009
6242009
Statistical outlier detection using direct density ratio estimation
S Hido, Y Tsuboi, H Kashima, M Sugiyama, T Kanamori
Knowledge and information systems 26, 309-336, 2011
2452011
Information geometry of U-Boost and Bregman divergence
N Murata, T Takenouchi, T Kanamori, S Eguchi
Neural Computation 16 (7), 1437-1481, 2004
2382004
Density-ratio matching under the bregman divergence: a unified framework of density-ratio estimation
M Sugiyama, T Suzuki, T Kanamori
Annals of the Institute of Statistical Mathematics 64, 1009-1044, 2012
2292012
Approximating mutual information by maximum likelihood density ratio estimation
T Suzuki, M Sugiyama, J Sese, T Kanamori
New challenges for feature selection in data mining and knowledge discovery …, 2008
1692008
Relative density-ratio estimation for robust distribution comparison
M Yamada, T Suzuki, T Kanamori, H Hachiya, M Sugiyama
Neural computation 25 (5), 1324-1370, 2013
1592013
Mutual information estimation reveals global associations between stimuli and biological processes
T Suzuki, M Sugiyama, T Kanamori, J Sese
BMC bioinformatics 10, 1-12, 2009
1512009
Statistical analysis of kernel-based least-squares density-ratio estimation
T Kanamori, T Suzuki, M Sugiyama
Machine Learning 86, 335-367, 2012
1262012
Relative density-ratio estimation for robust distribution comparison
M Yamada, T Suzuki, T Kanamori, H Hachiya, M Sugiyama
Advances in neural information processing systems 24, 2011
1222011
Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection
T Kanamori, S Hido, M Sugiyama
Advances in neural information processing systems 21, 2008
1052008
Least-squares conditional density estimation
M Sugiyama, I Takeuchi, T Suzuki, T Kanamori, H Hachiya, D Okanohara
IEICE Transactions on Information and Systems 93 (3), 583-594, 2010
962010
Density-difference estimation
M Sugiyama, T Kanamori, T Suzuki, MC Du Plessis, S Liu, I Takeuchi
Neural Computation 25 (10), 2734-2775, 2013
902013
Inlier-based outlier detection via direct density ratio estimation
S Hido, Y Tsuboi, H Kashima, M Sugiyama, T Kanamori
2008 Eighth IEEE international conference on data mining, 223-232, 2008
882008
Nonparametric conditional density estimation using piecewise-linear solution path of kernel quantile regression
I Takeuchi, K Nomura, T Kanamori
Neural Computation 21 (2), 533-559, 2009
792009
Conditional density estimation via least-squares density ratio estimation
M Sugiyama, I Takeuchi, T Suzuki, T Kanamori, H Hachiya, D Okanohara
Proceedings of the Thirteenth International Conference on Artificial …, 2010
752010
Active learning algorithm using the maximum weighted log-likelihood estimator
T Kanamori, H Shimodaira
Journal of statistical planning and inference 116 (1), 149-162, 2003
712003
A robust approach based on conditional value-at-risk measure to statistical learning problems
A Takeda, T Kanamori
European Journal of Operational Research 198 (1), 287-296, 2009
642009
Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search
M Sugiyama, M Yamada, P Von Buenau, T Suzuki, T Kanamori, ...
Neural Networks 24 (2), 183-198, 2011
582011
Least-squares two-sample test
M Sugiyama, T Suzuki, Y Itoh, T Kanamori, M Kimura
Neural networks 24 (7), 735-751, 2011
552011
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