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All publications by Arthur Gretton
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A low variance consistent test of relative dependency
Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus and Matthew Blaschko
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltan Szabo and Arthur Gretton
Advances in Neural Information Processing Systems 28, 2015


Fast Two-Sample Testing with Analytic Representations of Probability Measures
Kacper P. Chwialkowski, Aaditya Ramdas, Dino Sejdinovic and Arthur Gretton
Advances in Neural Information Processing Systems 28, 2015


Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria L. Garcia, Christophe Andrieu and Arthur Gretton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


A Kernel Independence Test for Random Processes
Kacper Chwialkowski and Arthur Gretton
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Kernel Mean Estimation and Stein Effect
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton and Bernhard Schölkopf
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


A Wild Bootstrap for Degenerate Kernel Tests
Kacper P. Chwialkowski, Dino Sejdinovic and Arthur Gretton
Advances in Neural Information Processing Systems 27, 2014


B-test: A Non-parametric, Low Variance Kernel Two-sample Test
Wojciech Zaremba, Arthur Gretton and Matthew Blaschko
Advances in Neural Information Processing Systems 26, 2013


A Kernel Test for Three-Variable Interactions
Dino Sejdinovic, Arthur Gretton and Wicher Bergsma
Advances in Neural Information Processing Systems 26, 2013


Optimal kernel choice for large-scale two-sample tests
Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu and Bharath K. Sriperumbudur
Advances in Neural Information Processing Systems 25, 2012


Hypothesis testing using pairwise distances and associated kernels
Dino Sejdinovic, Arthur Gretton, Kenji Fukumizu and Bharath K. Sriperumbudur
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Conditional mean embeddings as regressors
Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil and Steffen Grünewälder
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Modelling transition dynamics in MDPs with RKHS embeddings
Guy Lever, Luca Baldassarre, Arthur Gretton, Massimiliano Pontil and Steffen Grünewälder
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Kernel Bayes' Rule
Kenji Fukumizu, Le Song and Arthur Gretton
Advances in Neural Information Processing Systems 24, 2011


Kernel Belief Propagation
Le Song, Arthur Gretton, Danny Bickson, Yucheng Low and Carlos Guestrin
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees
Joseph Gonzalez, Yucheng Low, Arthur Gretton and Carlos Guestrin
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Nonparametric Tree Graphical Models
Le Song, Arthur Gretton and Carlos Guestrin
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Detecting the direction of causal time series
Jonas Peters, Dominik Janzing, Arthur Gretton and Bernhard Schölkopf
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Nonlinear directed acyclic structure learning with weakly additive noise models
Arthur Gretton, Peter Spirtes and Robert E. Tillman
Advances in Neural Information Processing Systems 22, 2009


A Fast, Consistent Kernel Two-Sample Test
Arthur Gretton, Kenji Fukumizu, Za\"ıd Harchaoui and Bharath K. Sriperumbudur
Advances in Neural Information Processing Systems 22, 2009


Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
Kenji Fukumizu, Arthur Gretton, Gert R. Lanckriet, Bernhard Schölkopf and Bharath K. Sriperumbudur
Advances in Neural Information Processing Systems 22, 2009


Tailoring density estimation via reproducing kernel moment matching
Le Song, Xinhua Zhang, Alex J. Smola, Arthur Gretton and Bernhard Schölkopf
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Kernel Measures of Independence for non-iid Data
Xinhua Zhang, Le Song, Arthur Gretton and Alex J. Smola
Advances in Neural Information Processing Systems 21, 2008


Learning Taxonomies by Dependence Maximization
Matthew Blaschko and Arthur Gretton
Advances in Neural Information Processing Systems 21, 2008


Characteristic Kernels on Groups and Semigroups
Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf and Bharath K. Sriperumbudur
Advances in Neural Information Processing Systems 21, 2008


Supervised feature selection via dependence estimation
Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt and Justin Bedo
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A dependence maximization view of clustering
Le Song, Arthur Gretton, Karsten M. Borgwardt and Alex J. Smola
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


A Kernel Statistical Test of Independence
Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


Kernel Measures of Conditional Dependence
Kenji Fukumizu, Arthur Gretton, Xiaohai Sun and Bernhard Schölkopf
Advances in Neural Information Processing Systems 20, 2007


Colored Maximum Variance Unfolding
Le Song, Arthur Gretton, Karsten M. Borgwardt and Alex J. Smola
Advances in Neural Information Processing Systems 20, 2007


Statistical Consistency of Kernel Canonical Correlation Analysis
Kenji Fukumizu, Francis R. Bach and Arthur Gretton
Journal of Machine Learning Research, 2007


Fast Kernel ICA using an Approximate Newton Method
Hao Shen, Stefanie Jegelka and Arthur Gretton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Correcting Sample Selection Bias by Unlabeled Data
Jiayuan Huang, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 19, 2006


A Kernel Method for the Two-Sample-Problem
Arthur Gretton, Karsten M. Borgwardt, Malte Rasch, Bernhard Schölkopf and Alex J. Smola
Advances in Neural Information Processing Systems 19, 2006


Statistical Convergence of Kernel CCA
Kenji Fukumizu, Arthur Gretton and Francis R. Bach
Advances in Neural Information Processing Systems 18, 2005


Kernel Methods for Measuring Independence
Arthur Gretton, Ralf Herbrich, Olivier Bousquet, Bernhard Schölkopf and Alex J. Smola
Journal of Machine Learning Research, 2005


Ranking on Data Manifolds
Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet and Bernhard Schölkopf
Advances in Neural Information Processing Systems 16, 2003