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Bharath Sriperumbudur
Bharath Sriperumbudur
Pennsylvania State University
Подтвержден адрес электронной почты в домене psu.edu - Главная страница
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Процитировано
Год
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
8942010
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
8922017
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
8262012
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
7992013
Universality, Characteristic Kernels and RKHS Embedding of Measures.
BK Sriperumbudur, K Fukumizu, GRG Lanckriet
Journal of Machine Learning Research 12 (7), 2011
5732011
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
4042018
On the empirical estimation of integral probability metrics
BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet
3712012
On the Convergence of the Concave-Convex Procedure.
BK Sriperumbudur, GRG Lanckriet
Nips 9, 1759-1767, 2009
3212009
A fast, consistent kernel two-sample test
A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur
Advances in neural information processing systems 22, 2009
2902009
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
2822009
On the convergence of the concave-convex procedure
G Lanckriet, BK Sriperumbudur
Advances in neural information processing systems 22, 2009
2822009
Learning theory for distribution regression
Z Szabó, BK Sriperumbudur, B Póczos, A Gretton
Journal of Machine Learning Research 17 (152), 1-40, 2016
1922016
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
1822008
Optimal rates for random Fourier features
B Sriperumbudur, Z Szabó
Advances in neural information processing systems 28, 2015
1622015
A majorization-minimization approach to the sparse generalized eigenvalue problem
BK Sriperumbudur, DA Torres, GRG Lanckriet
Machine learning 85, 3-39, 2011
1442011
Minimax estimation of maximum mean discrepancy with radial kernels
IO Tolstikhin, BK Sriperumbudur, B Schölkopf
Advances in Neural Information Processing Systems 29, 2016
1422016
Density estimation in infinite dimensional exponential families
B Sriperumbudur, K Fukumizu, A Gretton, A Hyv, R Kumar
Journal of Machine Learning Research 18 (57), 1-59, 2017
132*2017
Sparse eigen methods by dc programming
BK Sriperumbudur, DA Torres, GRG Lanckriet
Proceedings of the 24th international conference on Machine learning, 831-838, 2007
1192007
Characteristic kernels on groups and semigroups
K Fukumizu, A Gretton, B Schölkopf, BK Sriperumbudur
Advances in neural information processing systems 21, 2008
1172008
Two-stage sampled learning theory on distributions
Z Szabó, A Gretton, B Póczos, B Sriperumbudur
Artificial Intelligence and Statistics, 948-957, 2015
1052015
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Статьи 1–20