| 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 | 1075 | 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 | 871 | 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 | 860 | 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 | 804 | 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 | 767 | 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 | 752 | 2004 |
| Kernel measures of conditional dependence K Fukumizu, A Gretton, X Sun, B Schölkopf Advances in neural information processing systems 20, 2007 | 738 | 2007 |
| Universality, Characteristic Kernels and RKHS Embedding of Measures. BK Sriperumbudur, K Fukumizu, GRG Lanckriet Journal of Machine Learning Research 12 (7), 2011 | 554 | 2011 |
| Kernel dimension reduction in regression K Fukumizu, FR Bach, MI Jordan | 406 | 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 | 405 | 2009 |
| On the empirical estimation of integral probability metrics BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet | 359 | 2012 |
| Statistical consistency of kernel canonical correlation analysis. K Fukumizu, FR Bach, A Gretton Journal of Machine Learning Research 8 (2), 2007 | 347 | 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 | 289 | 2013 |
| A fast, consistent kernel two-sample test A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur Advances in neural information processing systems 22, 2009 | 279 | 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 | 277 | 2009 |
| Adaptive method of realizing natural gradient learning for multilayer perceptrons S Amari, H Park, K Fukumizu Neural computation 12 (6), 1399-1409, 2000 | 264 | 2000 |
| Local minima and plateaus in hierarchical structures of multilayer perceptrons K Fukumizu, S Amari Neural networks 13 (3), 317-327, 2000 | 255 | 2000 |
| Persistence weighted Gaussian kernel for topological data analysis G Kusano, Y Hiraoka, K Fukumizu International conference on machine learning, 2004-2013, 2016 | 234 | 2016 |
| On integral probability metrics,\phi-divergences and binary classification BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet arXiv preprint arXiv:0901.2698, 2009 | 231 | 2009 |
| Learning from distributions via support measure machines K Muandet, K Fukumizu, F Dinuzzo, B Schölkopf Advances in neural information processing systems 25, 2012 | 230 | 2012 |
Arthur GrettonGatsby Computational Neuroscience Unit and Google Deepmind確認したメール アドレス: gatsby.ucl.ac.uk
