A kernel statistical test of independence A Gretton, K Fukumizu, C Teo, L Song, B Schölkopf, A Smola Advances in neural information processing systems 20, 2007 | 1045 | 2007 |
Hilbert space embeddings and metrics on probability measures BK Sriperumbudur, A Gretton, K Fukumizu, B Schölkopf, GRG Lanckriet The Journal of Machine Learning Research 11, 1517-1561, 2010 | 850 | 2010 |
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 | 814 | 2017 |
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 25, 2012 | 757 | 2012 |
Equivalence of distance-based and RKHS-based statistics in hypothesis testing D Sejdinovic, B Sriperumbudur, A Gretton, K Fukumizu The annals of statistics, 2263-2291, 2013 | 746 | 2013 |
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 | 744 | 2004 |
Kernel measures of conditional dependence K Fukumizu, A Gretton, X Sun, B Schölkopf Advances in neural information processing systems 20, 2007 | 723 | 2007 |
Universality, Characteristic Kernels and RKHS Embedding of Measures. BK Sriperumbudur, K Fukumizu, GRG Lanckriet Journal of Machine Learning Research 12 (7), 2011 | 536 | 2011 |
Kernel dimension reduction in regression K Fukumizu, FR Bach, MI Jordan | 400 | 2009 |
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 | 394 | 2009 |
On the empirical estimation of integral probability metrics BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet | 350 | 2012 |
Statistical consistency of kernel canonical correlation analysis. K Fukumizu, FR Bach, A Gretton Journal of Machine Learning Research 8 (2), 2007 | 345 | 2007 |
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 | 282 | 2013 |
A fast, consistent kernel two-sample test A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur Advances in neural information processing systems 22, 2009 | 269 | 2009 |
Kernel choice and classifiability for RKHS embeddings of probability distributions K Fukumizu, A Gretton, G Lanckriet, B Schölkopf, BK Sriperumbudur Advances in neural information processing systems 22, 2009 | 266 | 2009 |
Adaptive method of realizing natural gradient learning for multilayer perceptrons S Amari, H Park, K Fukumizu Neural computation 12 (6), 1399-1409, 2000 | 263 | 2000 |
Local minima and plateaus in hierarchical structures of multilayer perceptrons K Fukumizu, S Amari Neural networks 13 (3), 317-327, 2000 | 253 | 2000 |
Persistence weighted Gaussian kernel for topological data analysis G Kusano, Y Hiraoka, K Fukumizu International conference on machine learning, 2004-2013, 2016 | 230 | 2016 |
Adaptive natural gradient learning algorithms for various stochastic models H Park, SI Amari, K Fukumizu Neural Networks 13 (7), 755-764, 2000 | 228 | 2000 |
Learning from distributions via support measure machines K Muandet, K Fukumizu, F Dinuzzo, B Schölkopf Advances in neural information processing systems 25, 2012 | 227 | 2012 |