| 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 | 509 | 2010 |
| 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 | 393 | 2013 |
| 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, 1205-1213, 2012 | 326 | 2012 |
| Kernel mean embedding of distributions: A review and beyond K Muandet, K Fukumizu, B Sriperumbudur, B Schölkopf arXiv preprint arXiv:1605.09522, 2016 | 288 | 2016 |
| Universality, Characteristic Kernels and RKHS Embedding of Measures. BK Sriperumbudur, K Fukumizu, GRG Lanckriet Journal of Machine Learning Research 12 (7), 2011 | 246 | 2011 |
| On the convergence of the concave-convex procedure BK Sriperumbudur, GRG Lanckriet Proceedings of the 22nd International Conference on Neural Information …, 2009 | 219 | 2009 |
| On the convergence of the concave-convex procedure G Lanckriet, BK Sriperumbudur Advances in neural information processing systems 22, 1759-1767, 2009 | 188 | 2009 |
| A fast, consistent kernel two-sample test A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur Advances in neural information processing systems 22, 673-681, 2009 | 163 | 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, 1750-1758, 2009 | 157 | 2009 |
| On the empirical estimation of integral probability metrics BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet Electronic Journal of Statistics 6, 1550-1599, 2012 | 156 | 2012 |
| 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 | 149 | 2008 |
| A majorization-minimization approach to the sparse generalized eigenvalue problem BK Sriperumbudur, DA Torres, GRG Lanckriet Machine learning 85 (1-2), 3-39, 2011 | 111 | 2011 |
| Sparse eigen methods by dc programming BK Sriperumbudur, DA Torres, GRG Lanckriet Proceedings of the 24th international conference on Machine learning, 831-838, 2007 | 103 | 2007 |
| Learning theory for distribution regression Z Szabó, BK Sriperumbudur, B Póczos, A Gretton The Journal of Machine Learning Research 17 (1), 5272-5311, 2016 | 84 | 2016 |
| Optimal rates for random fourier features B Sriperumbudur, Z Szabó Advances in Neural Information Processing Systems 28, 1144-1152, 2015 | 83 | 2015 |
| Characteristic kernels on groups and semigroups K Fukumizu, A Gretton, B Schölkopf, BK Sriperumbudur Advances in neural information processing systems 21, 473-480, 2008 | 80 | 2008 |
| Density estimation in infinite dimensional exponential families B Sriperumbudur, K Fukumizu, A Gretton, A Hyvärinen, R Kumar The Journal of Machine Learning Research 18 (1), 1830-1888, 2017 | 74* | 2017 |
| Generalization bounds for online learning algorithms with pairwise loss functions Y Wang, R Khardon, D Pechyony, R Jones Conference on Learning Theory, 13.1-13.22, 2012 | 71 | 2012 |
| Two-stage sampled learning theory on distributions Z Szabó, A Gretton, B Póczos, B Sriperumbudur Artificial Intelligence and Statistics, 948-957, 2015 | 68 | 2015 |
| Gaussian processes and kernel methods: A review on connections and equivalences M Kanagawa, P Hennig, D Sejdinovic, BK Sriperumbudur arXiv preprint arXiv:1807.02582, 2018 | 64 | 2018 |
Kenji FukumizuThe Institute of Statistical MathematicsVerified email at ism.ac.jp
