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Arthur Gretton

 

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Arthur Gretton

Position: Wissenschaftler  Abteilung: 

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Artikel (15):

Song L, Smola A, Gretton A, Bedo J und Borgwardt K (Mai-2012) Feature Selection via Dependence Maximization Journal of Machine Learning Research 13 1393-1434.
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Gretton A, Borgwardt K, Rasch M, Schölkopf B und Smola A (März-2012) A Kernel Two-Sample Test Journal of Machine Learning Research 13 723−773.
Blaschko MB, Shelton JA, Bartels A, Lampert CH und Gretton A (August-2011) Semi-supervised kernel canonical correlation analysis with application to human fMRI Pattern Recognition Letters 32(11) 1572-1583.
Thoma M, Cheng H, Gretton A, Han J, Kriegel H-P, Smola AJ, Song L, Yu PS, Yan X und Borgwardt KM (Oktober-2010) Discriminative frequent subgraph mining with optimality guarantees Statistical Analysis and Data Mining 3(5) 302–318.
Biessmann F, Meinecke FC, Gretton A, Rauch A, Rainer G, Logothetis NK und Müller K-R (Mai-2010) Temporal Kernel CCA and its Application in Multimodal Neuronal Data Analysis Machine Learning 79(1-2) 5-27.
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Sriperumbudur BK, Gretton A, Fukumizu K, Schölkopf B und Lanckriet GRG (April-2010) Hilbert Space Embeddings and Metrics on Probability Measures Journal of Machine Learning Research 11 1517-1561.
Shen H, Jegelka S und Gretton A (September-2009) Fast Kernel-Based Independent Component Analysis IEEE Transactions on Signal Processing 57(9) 3498-3511.
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Ku S-P, Gretton A, Macke J und Logothetis NK (September-2008) Comparison of Pattern Recognition Methods in Classifying High-resolution BOLD Signals Obtained at High Magnetic Field in Monkeys Magnetic Resonance Imaging 26(7) 1007-1014.
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Belitski A, Gretton A, Magri C, Murayama Y, Montemurro MA, Logothetis NK und Panzeri S (Mai-2008) Low-frequency Local Field Potentials and Spikes in Primary Visual Cortex Convey Independent Visual Information Journal of Neuroscience 28(22) 5696-5709.
Rasch MJ, Gretton A, Murayama Y, Maass W und Logothetis NK (März-2008) Inferring Spike Trains From Local Field Potentials Journal of Neurophysiology 99(3) 1461-1476.
Fukumizu K, Bach FR und Gretton A (Februar-2007) Statistical Consistency of Kernel Canonical Correlation Analysis Journal of Machine Learning Research 8 361-383.
Davy M, Desobry F, Gretton A und Doncarli C (August-2006) An Online Support Vector Machine for Abnormal Events Detection Signal Processing 86(8) 2009-2025.
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Gretton A, Belitski A, Murayama Y, Schölkopf B und Logothetis NK (April-2006) The Effect of Artifacts on Dependence Measurement in fMRI Magnetic Resonance Imaging 24(4) 401-409.
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Gretton A, Herbrich R, Smola A, Bousquet O und Schölkopf B (Dezember-2005) Kernel Methods for Measuring Independence Journal of Machine Learning Research 6 2075-2129.
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Davy M, Gretton A, Doucet A und Rayner PJW (Dezember-2002) Optimized Support Vector Machines for Nonstationary Signal Classification IEEE Signal Processing Letters 9(12) 442-445.
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Beiträge zu Tagungsbänden (39):

Sriperumbudur BK, Fukumizu K, Gretton A, Schölkopf B und Lanckriet GRG (Juni-2010) Non-parametric estimation of integral probability metrics, IEEE International Symposium on Information Theory (ISIT 2010), IEEE, Piscataway, NJ, USA, 1428-1432.
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Gretton A, Fukumizu K, Harchaoui Z und Sriperumbudur BK (April-2010) A Fast, Consistent Kernel Two-Sample Test In: Advances in Neural Information Processing Systems 22, , 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009), Curran, Red Hook, NY, USA, 673-681.
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Sriperumbudur BK, Fukumizu K, Gretton A, Lanckriet GRG und Schölkopf B (April-2010) Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions In: Advances in Neural Information Processing Systems 22, , 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009), Curran, Red Hook, NY, USA, 1750-1758.
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Tillman RE, Gretton A und Spirtes P (April-2010) Nonlinear directed acyclic structure learning with weakly additive noise models In: Advances in Neural Information Processing Systems 22, , 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009), Curran, Red Hook, NY, USA, 1847-1855.
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Peters J, Janzing D, Gretton A und Schölkopf B (2010) Kernel Methods for Detecting the Direction of Time Series In: Advances in Data Analysis, Data Handling and Business Intelligence, , 32nd Annual Conference of the Gesellschaft für Klassifikation e.V. (GfKl 2008), Springer, Berlin, Germany, 57-66, Series: Studies in Classification, Data Analysis, and Knowledge Organization.
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Jegelka S, Gretton A, Schölkopf B, Sriperumbudur BK und von Luxburg U (September-2009) Generalized Clustering via Kernel Embeddings In: KI 2009: Advances in Artificial Intelligence, , 32nd Annual Conference on Artificial Intelligence (KI), Springer, Berlin, Germany, 144-152, Series: Lecture Notes in Computer Science ; 5803.
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Fukumizu K, Sriperumbudur BK, Gretton A und Schölkopf B (Juni-2009) Characteristic Kernels on Groups and Semigroups In: Advances in neural information processing systems 21, , Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 473-480.
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Peters J, Janzing D, Gretton A und Schölkopf B (Juni-2009) Detecting the Direction of Causal Time Series, 26th International Conference on Machine Learning (ICML 2009), ACM Press, New York, NY, USA, 801-808.
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Zhang X, Song L, Gretton A und Smola A (Juni-2009) Kernel Measures of Independence for Non-IID Data In: Advances in neural information processing systems 21, , Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 1937-1944.
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Blaschko MB und Gretton A (Juni-2009) Learning Taxonomies by Dependence Maximization In: Advances in neural information processing systems 21, , Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 153-160.
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Thoma M, Cheng H, Gretton A, Han J, Kriegel H-P, Smola AJ, Song L, Yu PS, Yan X und Borgwardt KM (Mai-2009) Near-optimal supervised feature selection among frequent subgraphs, Ninth SIAM International Conference on Data Mining (SDM 2009), Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1076-1087.
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Gretton A und Györfi L (Oktober-2008) Nonparametric Independence Tests: Space Partitioning and Kernel Approaches In: Algorithmic Learning Theory, , 19th International Conference on Algorithmic Learning Theory (ALT 2008), Springer, Berlin, Germany, 183-198, Series: Lecture Notes in Computer Science ; 5254.
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Gretton A, Fukumizu K, Teo CH, Song L, Schölkopf B und Smola AJ (September-2008) A Kernel Statistical Test of Independence In: Advances in neural information processing systems 20, , Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Curran, Red Hook, NY, USA, 585-592.
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Song L, Smola AJ, Borgwardt K und Gretton A (September-2008) Colored Maximum Variance Unfolding In: Advances in neural information processing systems 20, , Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Curran, Red Hook, NY, USA, 1385-1392.
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Fukumizu K, Gretton A, Sun X und Schölkopf B (September-2008) Kernel Measures of Conditional Dependence In: Advances in neural information processing systems 20, , Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Curran, Red Hook, NY, USA, 489-496.
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Schölkopf B, Sriperumbudur BK, Gretton A und Fukumizu K (August-2008) RKHS Representation of Measures Applied to Homogeneity, Independence, and Fourier Optics, 30. Oberwolfach Report (OWR 2008), Mathematisches Forschungsinstitut, Oberwolfach-Walke, Germany, 42-44.
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Blaschko MB, Lampert CH und Gretton A (August-2008) Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis In: Machine Learning and Knowledge Discovery in Databases, , 19th European Conference on Machine Learning (ECML PKDD 2008), Springer, Berlin, Germany, 133-145, Series: Lecture Notes in Computer Science ; 5211.
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Blaschko MB und Gretton A (Juli-2008) A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery, 6th International Workshop on Mining and Learning with Graphs (MLG 2008), 1-3.
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Sriperumbudur BK, Gretton A, Fukumizu K, Lanckriet G und Schölkopf B (Juli-2008) Injective Hilbert Space Embeddings of Probability Measures, 21st Annual Conference on Learning Theory (COLT 2008), Omnipress, Madison, WI, USA, 111-122.
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Song L, Zhang X, Smola A, Gretton A und Schölkopf B (Juli-2008) Tailoring density estimation via reproducing kernel moment matching, 25th International Conference on Machine Learning (ICML 2008), ACM Press, New York, NY, USA, 992-999.
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Smola A, Gretton A, Song L und Schölkopf B (Oktober-2007) A Hilbert Space Embedding for Distributions In: Algorithmic Learning Theory, , 18th International Conference on Algorithmic Learning Theory (ALT 2007), Springer, Berlin, Germany, 13-31, Series: Lecture Notes in Computer Science ; 4754.
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Smola AJ, Gretton A, Song L und Schölkopf B (Oktober-2007) A Hilbert Space Embedding for Distributions In: Discovery Science, , 10th International Conference on Discovery Science (DS 2007), Springer, Berlin, Germany, 40-41, Series: Lecture Notes in Computer Science ; 4755.
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Gretton A, Borgwardt KM, Rasch M, Schölkopf B und Smola A (September-2007) A Kernel Method for the Two-Sample-Problem In: Advances in Neural Information Processing Systems 19, , Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), MIT Press, Cambridge, MA, USA, 513-520.
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Huang J, Smola A, Gretton A, Borgwardt KM und Schölkopf B (September-2007) Correcting Sample Selection Bias by Unlabeled Data In: Advances in Neural Information Processing Systems 19, , Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), MIT Press, Cambridge, MA, USA, 601-608.
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Gretton A, Borgwardt KM, Rasch M, Schölkopf B und Smola AJ (Juli-2007) A Kernel Approach to Comparing Distributions, Twenty-Second AAAI Conference on Artificial Intelligence (IAAI-07), AAAI Press, Menlo Park, CA, USA, 1637-1641.
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Song L, Bedo J, Borgwardt KM, Gretton A und Smola A (Juli-2007) Gene selection via the BAHSIC family of algorithms, 15th International Conference on Intelligent Systems for Molecular Biology (ISMB 2007), Bioinformatics, 23(13), i490-i498.
Song L, Smola AJ, Gretton A und Borgwardt KM (Juni-2007) A Dependence Maximization View of Clustering, 24th Annual International Conference on Machine Learning (ICML 2007), ACM Press, New York, NY, USA, 815-822.
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Song L, Smola AJ, Gretton A, Borgwardt KM und Bedo J (Juni-2007) Supervised Feature Selection via Dependence Estimation, 24th Annual International Conference on Machine Learning (ICML 2007), ACM Press, New York, NY, USA, 823-830.
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Shen H, Jegelka S und Gretton A (März-2007) Fast Kernel ICA using an Approximate Newton Method, 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), International Machine Learning Society, Madison, WI, USA, 476-483, Series: JMLR Workshop and Conference Proceedings ; 2.
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Borgwardt KM, Gretton A, Rasch M, Kriegel H-P, Schölkopf B und Smola A (August-2006) Integrating Structured Biological data by Kernel Maximum Mean Discrepancy, 14th International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Bioinformatics, 22(14), e49-e57.
Fukumizu K, Bach F und Gretton A (Mai-2006) Statistical Convergence of Kernel CCA In: Advances in neural information processing systems 18, , Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), MIT Press, Cambridge, MA, USA, 387-394.
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Gretton A, Bousquet O, Smola A und Schölkopf B (Oktober-2005) Measuring Statistical Dependence with Hilbert-Schmidt Norms In: Algorithmic Learning Theory, , 16th International Conference on Algorithmic Learning Theory (ALT 2005), Springer, Berlin, Germany, 63-78, Series: Lecture Notes in Computer Science ; 3734.
Gretton A, Smola AJ, Bousquet O, Herbrich R, Belitski A, Augath M, Murayama Y, Pauls J, Schölkopf B und Logothetis NK (Januar-2005) Kernel Constrained Covariance for Dependence Measurement, Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 2005), Society for Artificial Intelligence and Statistics, Fort Lauderdale, FL, USA, 112-119.
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BakIr G, Gretton A, Franz M und Schölkopf B (September-2004) Multivariate Regression via Stiefel Manifold Constraints In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 262-269, Series: Lecture Notes in Computer Science ; 3175.
Zhou D, Weston J, Gretton A, Bousquet O und Schölkopf B (Juni-2004) Ranking on Data Manifolds In: Advances in neural information processing systems 16, , Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 169-176.
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Last updated: Montag, 22.05.2017