Arthur Gretton

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Two-Sample Test. Journal of Machine Learning Research 13: 723-773 (2012)

Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton: Modelling transition dynamics in MDPs with RKHS embeddings. ICML 2012

Steffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil: Conditional mean embeddings as regressors. ICML 2012

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu: Hypothesis testing using pairwise distances and associated kernels. ICML 2012

Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu: Optimal kernel choice for large-scale two-sample tests. NIPS 2012: 1214-1222

Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu: Hilbert Space Embeddings of POMDPs. UAI 2012: 644-653

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu: Hypothesis testing using pairwise distances and associated kernels (with Appendix). CoRR abs/1205.0411 (2012)

Steffen Grünewälder, Guy Lever, Luca Baldassarre, Sam Patterson, Arthur Gretton, Massimiliano Pontil: Conditional mean embeddings as regressors - supplementary. CoRR abs/1205.4656 (2012)

Steffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton: Modelling transition dynamics in MDPs with RKHS embeddings. CoRR abs/1206.4655 (2012)

Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu: Equivalence of distance-based and RKHS-based statistics in hypothesis testing. CoRR abs/1207.6076 (2012)

Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu: Hilbert Space Embeddings of POMDPs. CoRR abs/1210.4887 (2012)

Joseph Gonzalez, Yucheng Low, Arthur Gretton, Carlos Guestrin: Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees. Journal of Machine Learning Research - Proceedings Track 15: 324-332 (2011)

Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin: Kernel Belief Propagation. Journal of Machine Learning Research - Proceedings Track 15: 707-715 (2011)

Matthew B. Blaschko, Jacquelyn A. Shelton, Andreas Bartels, Christoph H. Lampert, Arthur Gretton: Semi-supervised kernel canonical correlation analysis with application to human fMRI. Pattern Recognition Letters 32(11): 1572-1583 (2011)

Kenji Fukumizu, Le Song, Arthur Gretton: Kernel Bayes' Rule. NIPS 2011: 1737-1745

Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin: Kernel Belief Propagation. CoRR abs/1105.5592 (2011)

Steffen Grünewälder, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton, Guy Lever: Modeling transition dynamics in MDPs with RKHS embeddings of conditional distributions. CoRR abs/1112.4722 (2011)

Le Song, Arthur Gretton, Carlos Guestrin: Nonparametric Tree Graphical Models. Journal of Machine Learning Research - Proceedings Track 9: 765-772 (2010)

Arthur Gretton, László Györfi: Consistent Nonparametric Tests of Independence. Journal of Machine Learning Research 11: 1391-1423 (2010)

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet: Hilbert Space Embeddings and Metrics on Probability Measures. Journal of Machine Learning Research 11: 1517-1561 (2010)

Felix Bießmann, Frank C. Meinecke, Arthur Gretton, Alexander Rauch, Gregor Rainer, Nikos K. Logothetis, Klaus-Robert Müller: Temporal kernel CCA and its application in multimodal neuronal data analysis. Machine Learning 79(1-2): 5-27 (2010)

Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt: Discriminative frequent subgraph mining with optimality guarantees. Statistical Analysis and Data Mining 3(5): 302-318 (2010)

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf, Gert R. G. Lanckriet: Non-parametric estimation of integral probability metrics. ISIT 2010: 1428-1432

Somayeh Danafar, Arthur Gretton, Jürgen Schmidhuber: Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition. ECML/PKDD (1) 2010: 264-279

Hao Shen, Stefanie Jegelka, Arthur Gretton: Fast kernel-based independent component analysis. IEEE Transactions on Signal Processing 57(9): 3498-3511 (2009)

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Detecting the direction of causal time series. ICML 2009: 101

Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg: Generalized Clustering via Kernel Embeddings. KI 2009: 144-152

Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur: A Fast, Consistent Kernel Two-Sample Test. NIPS 2009: 673-681

Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert R. G. Lanckriet, Bernhard Schölkopf: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. NIPS 2009: 1750-1758

Robert E. Tillman, Arthur Gretton, Peter Spirtes: Nonlinear directed acyclic structure learning with weakly additive noise models. NIPS 2009: 1847-1855

Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt: Near-optimal Supervised Feature Selection among Frequent Subgraphs. SDM 2009: 1075-1086

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf: A note on integral probability metrics and $\phi$-divergences. CoRR abs/0901.2698 (2009)

Arthur Gretton, László Györfi: Nonparametric Independence Tests: Space Partitioning and Kernel Approaches. ALT 2008: 183-198

Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schölkopf: Injective Hilbert Space Embeddings of Probability Measures. COLT 2008: 111-122

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Kernel Methods for Detecting the Direction of Time Series. GfKl 2008: 57-66

Le Song, Xinhua Zhang, Alex J. Smola, Arthur Gretton, Bernhard Schölkopf: Tailoring density estimation via reproducing kernel moment matching. ICML 2008: 992-999

Matthew B. Blaschko, Arthur Gretton: Learning Taxonomies by Dependence Maximization. NIPS 2008: 153-160

Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schölkopf: Characteristic Kernels on Groups and Semigroups. NIPS 2008: 473-480

Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smola: Kernel Measures of Independence for non-iid Data. NIPS 2008: 1937-1944

Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton: Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis. ECML/PKDD (1) 2008: 133-145

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Method for the Two-Sample Problem. CoRR abs/0805.2368 (2008)

Hao Shen, Stefanie Jegelka, Arthur Gretton: Fast Kernel ICA using an Approximate Newton Method. Journal of Machine Learning Research - Proceedings Track 2: 476-483 (2007)

Kenji Fukumizu, Francis R. Bach, Arthur Gretton: Statistical Consistency of Kernel Canonical Correlation Analysis. Journal of Machine Learning Research 8: 361-383 (2007)

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Approach to Comparing Distributions. AAAI 2007: 1637-1641

Alex J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf: A Hilbert Space Embedding for Distributions. ALT 2007: 13-31

Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf: A Hilbert Space Embedding for Distributions. Discovery Science 2007: 40-41

Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt: A dependence maximization view of clustering. ICML 2007: 815-822

Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo: Supervised feature selection via dependence estimation. ICML 2007: 823-830

Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola: Gene selection via the BAHSIC family of algorithms. ISMB/ECCB (Supplement of Bioinformatics) 2007: 490-498

Kenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf: Kernel Measures of Conditional Dependence. NIPS 2007

Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alex J. Smola: A Kernel Statistical Test of Independence. NIPS 2007

Le Song, Alex J. Smola, Karsten M. Borgwardt, Arthur Gretton: Colored Maximum Variance Unfolding. NIPS 2007

Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo: Supervised Feature Selection via Dependence Estimation. CoRR abs/0704.2668 (2007)

Manuel Davy, Frédéric Desobry, Arthur Gretton, Christian Doncarli: An online support vector machine for abnormal events detection. Signal Processing 86(8): 2009-2025 (2006)

Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola: Integrating structured biological data by Kernel Maximum Mean Discrepancy. ISMB (Supplement of Bioinformatics) 2006: 49-57

Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola: A Kernel Method for the Two-Sample-Problem. NIPS 2006: 513-520

Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf: Correcting Sample Selection Bias by Unlabeled Data. NIPS 2006: 601-608

Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf: Kernel Methods for Measuring Independence. Journal of Machine Learning Research 6: 2075-2129 (2005)

Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf: Measuring Statistical Dependence with Hilbert-Schmidt Norms. ALT 2005: 63-77

Kenji Fukumizu, Francis R. Bach, Arthur Gretton: Statistical Convergence of Kernel CCA. NIPS 2005

Gökhan H. Bakir, Arthur Gretton, Matthias O. Franz, Bernhard Schölkopf: Multivariate Regression via Stiefel Manifold Constraints. DAGM-Symposium 2004: 262-269

Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf: Ranking on Data Manifolds. NIPS 2003