Professor, Intelligent Information Processing Group, Department of Statistical Modeling
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Kenji FUKUMIZU
Professor, Intelligent Information Processing Group, Department of Statistical Modeling |
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Selected Papers Membership of Academic Societies Professional Services
(1) Sriperumbudur, B., Fukumizu, K., Gretton, A., Lanckriet, G., and Scholkopf, B. (2010):
Kernel choice and classifiability for RKHS embeddings of probability distributions.
Advances in Neural Information Processing Systems 22. to appear.
(2) Gretton, A., Harchaoui, Z., Fukumizu, K., Sriperumbudur, B. (2010):
A fast, consistent Kernel two-sample test.
Advances in Neural Information Processing Systems 22. to appear.
(3) Watanabe, Y., and Fukumizu, K. (2010):
Graph zeta function in the Bethe free energy and loopy belief propagation.
Advances in Neural Information Processing Systems 22. to appear.
(4) Watanabe, Y., and Fukumizu, K. (2009): Loop series expansion with propagation diagrams
Journal of Physics A: Mathematical and Theoretical 42, 045001, 18pp.
(5) Fukumizu, K. (2008): Exponential manifold by reproducing kernel Hilbert spaces.
in Algebraic and Geometric mothods in statistics (P.Gibilisco, E.Riccomagno, M.-P.Rogantin, and Henry Winn eds.)
Cambridge University Press, 291-306
(6) Fukumizu, K. F.R. Bach and M. I. Jordan. (2008): Kernel dimension reduction in regression.
The Annals of Statistics, 37(4), 1871-1905.
(7) Fukumizu, K., Sriperumbudur, B., Gretton, A., and Scholkopf, B. (2008):
Characteristic Kernels on groups and semigroups.
Advances in Neural Information Processing Systems 21, 473-480
(8) Fukumizu, K., A. Gretton, X. Sun, and B. Schoelkopf (2008):
Kernel Measures of Conditional Dependence.
Advances in Neural Information Processing Systems
21, 489-496.
(9) Gretton, A. Fukumizu, K. Teo,C.H., Song, L., Schoelkopf, B., and Smola, A. (2008):
A Kernel Statistical Test of Independence.
Advances in Neural Information Processing Systems
21, 585-592.
(10) Fukumizu, K. (2008): Statistical estimation with positive definite kernels.
in Statistical Science in the 21th Century III (G. Kitagawa and A. Takemura eds.), 257-290.
University of Tokyo Press. (in Japanese)
(11) Shiraishi, Y. and Fukumizu, K. (2008): Game theoretical combination of binary classifiers
for multi-class classification.
IEICE Transactions on Information and Systems Vol.J91-D No.6, 1528-1537 (in Japanese)
(12) Fukumizu, K., F. R. Bach and A. Gretton. (2007):
Statistical consistency of kernel canonical correlation analysis,
Journal of Machine Learning Research,
8,
361-383.
(13) Marco Cuturi, Kenji Fukumizu, and Jean-Philippe Vert (2005):
Semigroup Kernels on Measures, Journal of Machine Learning Research,
6, 1169-1198.
(14) Watanabe, S., Fukumizu, K., Hagiwara, K., and Amari, S. (2005):
Learning Theory of Singular Models, The IEICE Transactoins
J88-D2 (2), 159-169 (in Japanese)
(15) Fukumizu, K., Bach, F.R., and Jordan, M.I. (2004): Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces,
Journal of Machine Learning Research,
5, 73-99.
(16) Fukumizu, K. and Akaho, S. and Amari, S. (2003): Critical lines in symmetry of mixture models and its application to component
splitting, Advances in NIPS, 15, 865-872.
(17) Fukumizu, K. and Kuriki, S. (2003): Statistical inference in singular models - an approach by tangent cone -,
(18) Fukumizu, K. (2003): Likelihood ratio of unidentifiable models and multilayer neural networks, Annals
of Statistics, 31 (3), 833-851.
(19) Fukumizu, K. (2001): Geometry of neural networks: Natural gradient for learning, Handbook of
Biological Physics, vol.4: Neuro-informatics and Neural Modelling, Elesvier, 731-769.
(20) Fukumizu, K. and Amari, S. (2000): Local minima and plateaus in hierarchical structures of multilayer perceptrons,
Neural Networks, 13 (3), 317-327.
(21) Fukumizu, K. (2000): Statistical active learning in multilayer perceptrons, IEEE Trans. Neural
Networks, 11 (1), 17-26.
(22) Amari, S., Park, H., and Fukumizu, K. (2000): Adaptive method of realizing natural gradient learning for multilayer perceptrons,
Neural Computation,
12 (6), 1399-1409.
(23) Fukumizu, K. (1999): Generalization error of linear neural networks in unidentifiable cases,
Lecture Notes in Artificial Intelligence 1720, Algorithmic Learning Theory,
Springer Verlag, 51-62.
(24) Fukumizu, K. (1997): Active learning in neural networks, Journal of IPSJ,
8 (7), 569-574 (in Japanese).
(25) Fukumizu, K. (1996): A regularity condition of the information matrix of a multilayer perceptron
network, Neural Networks, 9 (5), 871-879.
(26) Ishii, S., Watanabe, S. and Fukumizu, K. (1996): A network of chaotic elements for information processing,
Neural Networks, 9 (1), 25-40.
(27) Fukumizu, K. (1996): Active learning in multilayer perceptrons, Advances in NIPS,
8, 295-301.
(28) Fukumizu, K. and Watanabe, S. (1996): Optimal training data and predictive error of polynomial approximation, Trans.
IEICE, Vol.J79-A(5), 1100-1108 (in Japanese).
(29) Watanabe, S. and Fukumizu, K. (1995): Probabilistic design of layered neural networks based on their unified framework,
IEEE Trans. Neural Networks,
6 (3), 691-702.
Selected Publications
(1) Neural Network Systems Techniques
and Applications 1: Algorithms and Archtechtures, Academic Press (1997).
(2) Statistical Theory of Singular Models,
Iwanami Shoten (2004). (in Japanese)
(3) Theory and Practice of Learning Systems,
Morikita-Shuppan. (2005). (in Japanese)
The Institute of Electronics, Information
and Communication Engineers; Japanese Neural Network Society; The Institute
of Mathematical Statistics
Neural Networks, Associate
editor. Foundations and Trends in Machine Learning, Editorial Board.
Annals of the Institute of Statistical Mathematics, Associate
editor. Technical group on Information-based Induction Sciences. The Institute
of Electronics. Information and Communication Engineers, Commissioner.
