arthur gretton
arthur gretton
Gatsby Computational Neuroscience Unit, UCL
Email verificata su - Home page
Citata da
Citata da
A kernel two-sample test
A Gretton, KM Borgwardt, MJ Rasch, B Schölkopf, A Smola
The Journal of Machine Learning Research 13 (1), 723-773, 2012
Correcting sample selection bias by unlabeled data
J Huang, A Gretton, K Borgwardt, B Schölkopf, A Smola
Advances in neural information processing systems 19, 601-608, 2006
A kernel method for the two-sample-problem
A Gretton, K Borgwardt, M Rasch, B Schölkopf, A Smola
Advances in neural information processing systems 19, 513-520, 2006
Measuring statistical dependence with Hilbert-Schmidt norms
A Gretton, O Bousquet, A Smola, B Schölkopf
International conference on algorithmic learning theory, 63-77, 2005
Ranking on data manifolds
D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf
Advances in neural information processing systems 16, 169-176, 2004
Integrating structured biological data by kernel maximum mean discrepancy
KM Borgwardt, A Gretton, MJ Rasch, HP Kriegel, B Schölkopf, AJ Smola
Bioinformatics 22 (14), e49-e57, 2006
A Hilbert space embedding for distributions
A Smola, A Gretton, L Song, B Schölkopf
International Conference on Algorithmic Learning Theory, 13-31, 2007
A kernel statistical test of independence.
A Gretton, K Fukumizu, CH Teo, L Song, B Schölkopf, AJ Smola
Nips 20, 585-592, 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
Covariate shift by kernel mean matching
A Gretton, A Smola, J Huang, M Schmittfull, K Borgwardt, B Schölkopf
Dataset shift in machine learning 3 (4), 5, 2009
Kernel measures of conditional dependence.
K Fukumizu, A Gretton, X Sun, B Schölkopf
NIPS 20, 489-496, 2007
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
Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information
A Belitski, A Gretton, C Magri, Y Murayama, MA Montemurro, ...
Journal of Neuroscience 28 (22), 5696-5709, 2008
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, 1205-1213, 2012
Kernel methods for measuring independence
A Gretton, R Herbrich, A Smola, O Bousquet, B Schölkopf
MIT Press, 2005
Feature selection via dependence maximization.
L Song, A Smola, A Gretton, J Bedo, K Borgwardt
Journal of Machine Learning Research 13 (5), 2012
Supervised feature selection via dependence estimation
L Song, A Smola, A Gretton, KM Borgwardt, J Bedo
Proceedings of the 24th international conference on Machine learning, 823-830, 2007
Demystifying mmd gans
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
arXiv preprint arXiv:1801.01401, 2018
Statistical Consistency of Kernel Canonical Correlation Analysis.
K Fukumizu, FR Bach, A Gretton
Journal of Machine Learning Research 8 (2), 2007
Inferring spike trains from local field potentials
MJ Rasch, A Gretton, Y Murayama, W Maass, NK Logothetis
Journal of neurophysiology 99 (3), 1461-1476, 2008
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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