Kenji Fukumizu
Kenji Fukumizu
Verified email at ism.ac.jp - Homepage
TitleCited byYear
Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces
K Fukumizu, FR Bach, MI Jordan
Journal of Machine Learning Research 5 (Jan), 73-99, 2004
5052004
A kernel statistical test of independence
A Gretton, K Fukumizu, CH Teo, L Song, B Schölkopf, AJ Smola
Advances in neural information processing systems, 585-592, 2008
4362008
Hilbert space embeddings and metrics on probability measures
BK Sriperumbudur, A Gretton, K Fukumizu, B Schölkopf, GRG Lanckriet
Journal of Machine Learning Research 11 (Apr), 1517-1561, 2010
3842010
Kernel measures of conditional dependence
K Fukumizu, A Gretton, X Sun, B Schölkopf
Advances in neural information processing systems, 489-496, 2008
3492008
Equivalence of distance-based and RKHS-based statistics in hypothesis testing
D Sejdinovic, B Sriperumbudur, A Gretton, K Fukumizu
The Annals of Statistics 41 (5), 2263-2291, 2013
2762013
Kernel dimension reduction in regression
K Fukumizu, FR Bach, MI Jordan
The Annals of Statistics 37 (4), 1871-1905, 2009
2582009
Statistical consistency of kernel canonical correlation analysis
K Fukumizu, FR Bach, A Gretton
Journal of Machine Learning Research 8 (Feb), 361-383, 2007
2182007
Optimal kernel choice for large-scale two-sample tests
A Gretton, D Sejdinovic, H Strathmann, S Balakrishnan, M Pontil, ...
Advances in neural information processing systems, 1205-1213, 2012
2082012
Adaptive method of realizing natural gradient learning for multilayer perceptrons
SI Amari, H Park, K Fukumizu
Neural Computation 12 (6), 1399-1409, 2000
2002000
Hilbert space embeddings of conditional distributions with applications to dynamical systems
L Song, J Huang, A Smola, K Fukumizu
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
1792009
Adaptive natural gradient learning algorithms for various stochastic models
H Park, SI Amari, K Fukumizu
Neural Networks 13 (7), 755-764, 2000
1652000
Universality, characteristic kernels and RKHS embedding of measures
BK Sriperumbudur, K Fukumizu, GRG Lanckriet
Journal of Machine Learning Research 12 (Jul), 2389-2410, 2011
1612011
Local minima and plateaus in hierarchical structures of multilayer perceptrons
K Fukumizu, S Amari
Neural networks 13 (3), 317-327, 2000
1612000
Kernel mean embedding of distributions: A review and beyond
K Muandet, K Fukumizu, B Sriperumbudur, B Schölkopf
Foundations and Trends® in Machine Learning 10 (1-2), 1-141, 2017
1602017
Learning from distributions via support measure machines
K Muandet, K Fukumizu, F Dinuzzo, B Schölkopf
Advances in neural information processing systems, 10-18, 2012
1302012
A fast, consistent kernel two-sample test
A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur
Advances in neural information processing systems, 673-681, 2009
1292009
Kernel choice and classifiability for RKHS embeddings of probability distributions
K Fukumizu, A Gretton, GR Lanckriet, B Schölkopf, BK Sriperumbudur
Advances in neural information processing systems, 1750-1758, 2009
1272009
Injective Hilbert space embeddings of probability measures
BK Sriperumbudur, A Gretton, K Fukumizu, G Lanckriet, B Schölkopf
21st Annual Conference on Learning Theory (COLT 2008), 111-122, 2008
1252008
Kernel embeddings of conditional distributions: A unified kernel framework for nonparametric inference in graphical models
L Song, K Fukumizu, A Gretton
IEEE Signal Processing Magazine 30 (4), 98-111, 2013
1222013
Statistical active learning in multilayer perceptrons
K Fukumizu
IEEE Transactions on Neural Networks 11 (1), 17-26, 2000
1192000
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Articles 1–20