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Bharath Sriperumbudur
Bharath Sriperumbudur
Pennsylvania State University
Bestätigte E-Mail-Adresse bei psu.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
9142017
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
9102010
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
8452012
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
8162013
Universality, Characteristic Kernels and RKHS Embedding of Measures.
BK Sriperumbudur, K Fukumizu, GRG Lanckriet
Journal of Machine Learning Research 12 (7), 2011
5862011
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
4172018
On the empirical estimation of integral probability metrics
BK Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf, GRG Lanckriet
3752012
On the Convergence of the Concave-Convex Procedure.
BK Sriperumbudur, GRG Lanckriet
Nips 9, 1759-1767, 2009
3222009
A fast, consistent kernel two-sample test
A Gretton, K Fukumizu, Z Harchaoui, BK Sriperumbudur
Advances in neural information processing systems 22, 2009
2952009
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
2862009
On the convergence of the concave-convex procedure
G Lanckriet, BK Sriperumbudur
Advances in neural information processing systems 22, 2009
2862009
Learning theory for distribution regression
Z Szabó, BK Sriperumbudur, B Póczos, A Gretton
Journal of Machine Learning Research 17 (152), 1-40, 2016
1952016
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
1872008
Optimal rates for random Fourier features
B Sriperumbudur, Z Szabó
Advances in neural information processing systems 28, 2015
1702015
Minimax estimation of maximum mean discrepancy with radial kernels
IO Tolstikhin, BK Sriperumbudur, B Schölkopf
Advances in Neural Information Processing Systems 29, 2016
1542016
A majorization-minimization approach to the sparse generalized eigenvalue problem
BK Sriperumbudur, DA Torres, GRG Lanckriet
Machine learning 85, 3-39, 2011
1472011
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
135*2017
Characteristic kernels on groups and semigroups
K Fukumizu, A Gretton, B Schölkopf, BK Sriperumbudur
Advances in neural information processing systems 21, 2008
1202008
Sparse eigen methods by dc programming
BK Sriperumbudur, DA Torres, GRG Lanckriet
Proceedings of the 24th international conference on Machine learning, 831-838, 2007
1202007
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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