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Publications of Arthur Gretton
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70 total
result as bibtex
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Journal Articles (12)
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Biessmann, F., F. C. Meinecke, A. Gretton, A. Rauch, G. Rainer, N. K. Logothetis and K.-R. Müller: Temporal Kernel CCA and its Application in Multimodal Neuronal Data Analysis. Machine Learning (accepted) (11 2009)
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Shen, H., S. Jegelka and A. Gretton: Fast Kernel-Based Independent Component Analysis. IEEE Transactions on Signal Processing 57(9), 3498-3511 (09 2009)
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Ku, S.-P., A. Gretton, J. Macke and N. K. Logothetis: 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 (09 2008)
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Belitski, A., A. Gretton, C. Magri, Y. Murayama, M. A. Montemurro, N. K. Logothetis and S. Panzeri: Low-frequency Local Field Potentials and Spikes in Primary Visual Cortex Convey Independent Visual Information. Journal of Neuroscience 28(22), 5696-5709 (05 2008)
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Rasch, M. J., A. Gretton, Y. Murayama, W. Maass and N. K. Logothetis: Inferring Spike Trains From Local Field Potentials. Journal of Neurophysiology 99(3), 1461-1476 (03 2008)
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Song, L., J. Bedo, K. M. Borgwardt, A. Gretton and A. Smola: Gene selection via the BAHSIC family of algorithms. Bioinformatics 23(13), i490-i498 (07 2007)
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Fukumizu, K., F. R. Bach and A. Gretton: Statistical Consistency of Kernel Canonical Correlation Analysis. Journal of Machine Learning Research 8, 361-383 (02 2007)
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Borgwardt, K., A. Gretton, M. Rasch, H.-P. Kriegel, B. Schölkopf and A. Smola: Integrating Structured Biological data by Kernel Maximum Mean Discrepancy. Bioinformatics 22(4), e49-e57 (08 2006)
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Davy, M., F. Desobry, A. Gretton and C. Doncarli: An Online Support Vector Machine for Abnormal Events Detection. Signal Processing 86(8), 2009-2025 (08 2006)
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Gretton, A., A. Belitski, Y. Murayama, B. Schölkopf and N. K. Logothetis: The Effect of Artifacts on Dependence Measurement in fMRI. Magnetic Resonance Imaging 24(4), 401-409 (04 2006)
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Gretton, A., R. Herbrich, A. Smola, O. Bousquet and B. Schölkopf: Kernel Methods for Measuring Independence. Journal of Machine Learning Research 6, 2075-2129 (12 2005)
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Davy, M., A. Gretton, A. Doucet and P. J.W. Rayner: Optimized Support Vector Machines for Nonstationary Signal Classification. IEEE Signal Processing Letters 9(12), 442-445 (12 2002)
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Conference Papers (35)
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Gretton, A., K. Fukumizu, Z. Harchaoui and B. K. Sriperumbudur: A Fast, Consistent Kernel Two-Sample Test. Advances in Neural Information Processing Systems 22: Proceedings of the 2009 Conference (NIPS 2009), 673-681. (Eds.) Bengio, Y., D. Schuurmans, J. Lafferty, C. Williams, A. Culotta (01 2010)
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Sriperumbudur, B. K., K. Fukumizu, A. Gretton, G. R.G. Lanckriet and B. Schölkopf: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions. Advances in Neural Information Processing Systems 22: Proceedings of the 2009 Conference (NIPS 2009), 1750-1758. (Eds.) Bengio, Y., D. Schuurmans, J. Lafferty, C. Williams, A. Culotta (01 2010)
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Tillman, R. E., A. Gretton and P. Spirtes: Nonlinear directed acyclic structure learning with weakly additive noise models. Advances in Neural Information Processing Systems 22: Proceedings of the 2009 Conference (NIPS 2009), 1847-1855. (Eds.) Bengio, Y., D. Schuurmans, J. Lafferty, C. Williams, A. Culotta (01 2010)
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Peters, J., D. Janzing, A. Gretton and B. Schölkopf: Kernel Methods for Detecting the Direction of Time Series. Advances in Data Analysis, Data Handling and Business Intelligence, 57-66. (Eds.) Fink, A., B. Lausen, W. Seidel, A. Ultsch, Springer, Berlin, Germany (10 2009)
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Jegelka, S., A. Gretton, B. Schölkopf, B. K. Sriperumbudur and U. von Luxburg: Generalized Clustering via Kernel Embeddings. KI 2009: Advances in Artificial Intelligence, 144-152. (Eds.) Mertsching, B., M. Hund, Z. Aziz, Springer, Berlin, Germany (09 2009)
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Blaschko, M. B. and A. Gretton: Learning Taxonomies by Dependence Maximization. Advances in Neural Information Processing Systems 21: Proceedings of the 2008 Conference, 153-160. (Eds.) Koller, D., D. Schuurmans, Y. Bengio, L. Bottou, Curran, Red Hook, NY, USA (06 2009)
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Fukumizu, K., B. K. Sriperumbudur, A. Gretton and B. Schölkopf: Characteristic Kernels on Groups and Semigroups. Advances in Neural Information Processing Systems 21: Proceedings of the 2008 Conference, 473-480. (Eds.) Koller, D., D. Schuurmans, Y. Bengio, L. Bottou, Curran, Red Hook, NY, USA (06 2009)
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Peters, J., D. Janzing, A. Gretton and B. Schölkopf: Detecting the Direction of Causal Time Series. Proceedings of the 26th International Conference on Machine Learning (ICML 2009), 801-808. (Eds.) Danyluk, A., L. Bottou, M. L. Littman, ACM Press, New York, NY, USA (06 2009)
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Zhang, X., L. Song, A. Gretton and A. Smola: Kernel Measures of Independence for Non-IID Data. Advances in Neural Information Processing Systems 21: Proceedings of the 2008 Conference, 1937-1944. (Eds.) Koller, D., D. Schuurmans, Y. Bengio, L. Bottou, Curran, Red Hook, NY, USA (06 2009)
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Thoma, M., H. Cheng, A. Gretton, J. Han, H.-P. Kriegel, A. J. Smola, L. Song, P. S. Yu, X. Yan and K. M. Borgwardt: Near-optimal supervised feature selection among frequent subgraphs. Proccedings of the 2009 SIAM Conference on Data Mining (SDM 2009), 1076-1087. (Eds.) Park, H., S. Parthasarathy, H. Liu, Philadelphia, PA, USA, Society for Industrial and Applied Mathematics (05 2009)
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Gretton, A. and L. Györfi: Nonparametric Independence Tests: Space Partitioning and Kernel Approaches. Algorithmic Learning Theory: 19th International Conference (ALT08), 183-198. (Eds.) Freund, Y., L. Györfi, G. Turán, T. Zeugmann, Springer, Berlin, Germany (10 2008)
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Fukumizu, K., A. Gretton, X. Sun and B. Schölkopf: Kernel Measures of Conditional Dependence. Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference, 489-496. (Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, Curran, Red Hook, NY, USA (09 2008)
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Gretton, A., K. Fukumizu, C. H. Teo, L. Song, B. Schölkopf and A. J. Smola: A Kernel Statistical Test of Independence. Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference, 585-592. (Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, Curran, Red Hook, NY, USA (09 2008)
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Song, L., A. J. Smola, K. Borgwardt and A. Gretton: Colored Maximum Variance Unfolding. Advances in Neural Information Processing Systems 20: Proceedings of the 2007 Conference, 1385-1392. (Eds.) Platt, J. C., D. Koller, Y. Singer, S. Roweis, Curran, Red Hook, NY, USA (09 2008)
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Blaschko, M. B., C. H. Lampert and A. Gretton: Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2008, 133-145. (Eds.) Daelemans, W., B. Goethals, K. Morik, Springer, Berlin, Germany (08 2008)
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Schölkopf, B., B. K. Sriperumbudur, A. Gretton and K. Fukumizu: RKHS Representation of Measures Applied to Homogeneity, Independence, and Fourier Optics. 30. Oberwolfach Report (OWR 2008), 42-44. (Eds.) Jetter, K., S. Smale, D.-X. Zhou, Mathematisches Forschungsinstitut, Oberwolfach-Walke, Germany (08 2008)
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Blaschko, M. B. and A. Gretton: A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery. Proceedings of the 6th International Workshop on Mining and Learning with Graphs (MLG 2008), 1-3 (07 2008)
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Song, L., X. Zhang, A. Smola, A. Gretton and B. Schölkopf: Tailoring density estimation via reproducing kernel moment matching. Proceedings of the 25th International Conference on Machine Learning (ICML 2008), 992-999. (Eds.) Cohen, W. W., A. McCallum, S. Roweis, ACM Press, New York, NY, USA (07 2008)
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Sriperumbudur, B. K., A. Gretton, K. Fukumizu, G. Lanckriet and B. Schölkopf: Injective Hilbert Space Embeddings of Probability Measures. Proceedings of the 21st Annual Conference on Learning Theory (COLT 2008), 111-122. (Eds.) Servedio, R. A., T. Zhang, Omnipress, Madison, WI, USA (07 2008)
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Smola, A., A. Gretton, L. Song and B. Schölkopf: A Hilbert Space Embedding for Distributions. Algorithmic Learning Theory: 18th International Conference (ALT 2007), 13-31. (Eds.) Hutter, M., R. A. Servedio, E. Takimoto, Springer, Berlin, Germany (10 2007)
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Gretton, A., K. M. Borgwardt, M. Rasch, B. Schölkopf and A. Smola: A Kernel Method for the Two-Sample-Problem. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, 513-520. (Eds.) Schölkopf, B., J. Platt, T. Hofmann, MIT Press, Cambridge, MA, USA (09 2007)
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Huang, J., A. Smola, A. Gretton, K. M. Borgwardt and B. Schölkopf: Correcting Sample Selection Bias by Unlabeled Data. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, 601-608. (Eds.) Schölkopf, B., J. Platt, T. Hofmann, MIT Press, Cambridge, MA, USA (09 2007)
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Gretton, A., K. M. Borgwardt, M. Rasch, B. Schölkopf and A. J. Smola: A Kernel Approach to Comparing Distributions. Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), 1637-1641, AAAI Press, Menlo Park, CA, USA (07 2007)
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Song, L., A. J. Smola, A. Gretton and K. M. Borgwardt: A Dependence Maximization View of Clustering. Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), 815-822. (Eds.) Ghahramani, Z. ACM Press, New York, NY, USA (06 2007)
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Song, L., A. J. Smola, A. Gretton, K. M. Borgwardt and J. Bedo: Supervised Feature Selection via Dependence Estimation. Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), 823-830. (Eds.) Ghahramani, Z. ACM Press, New York, NY, USA (06 2007)
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Shen, H., S. Jegelka and A. Gretton: Fast Kernel ICA using an Approximate Newton Method. Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), 476-483. (Eds.) Meila, M., X. Shen, Microtome, Brookline, MA, USA (03 2007)
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Fukumizu, K., F. Bach and A. Gretton: Statistical Convergence of Kernel CCA. Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, 387-394. (Eds.) Weiss, Y., B. Schölkopf, J. Platt, MIT Press, Cambridge, MA, USA (05 2006)
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Gretton, A., O. Bousquet, A. Smola and B. Schoelkopf: Measuring Statistical Dependence with Hilbert-Schmidt Norms. Algorithmic Learning Theory: 16th International Conference, ALT 2005, 63-78 (10/08/ 2005)
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Gretton, A., A. J. Smola, O. Bousquet, R. Herbrich, A. Belitski, M. Augath, Y. Murayama, J. Pauls, B. Schölkopf and N. K. Logothetis: Kernel Constrained Covariance for Dependence Measurement. AISTATS 2005 10, 1-8 (01 2005)
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BakIr, G., A. Gretton, M. Franz and B. Schölkopf: Multivariate Regression via Stiefel Manifold Constraints. Pattern Recognition, Proceedings of the 26th DAGM Symposium, 262-269. (Eds.) Rasmussen, C., Bülthoff, M. A. Giese, Springer, Berlin, Germany (2004)
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Zhou, D., J. Weston, A. Gretton, O. Bousquet and B. Schölkopf: Ranking on Data Manifolds. Advances in Neural Information Processing Systems 16, 169-176. (Eds.) Thrun, S., L. Saul and B. Schölkopf, MIT Press, Cambridge, MA, USA (2004)
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Gretton, A. and Desobry: On-Line One-Class Support Vector Machines. An Application to Signal Segmentation. IEEE ICASSP Vol. 2, 709-712 (04 2003)
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Gretton, A., Herbrich and A. Smola: The Kernel Mutual Information. IEEE ICASSP Vol. 4, 880-883 (04 2003)
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Arthur Gretton, Manuel Davy, Arnaud Doucet and Peter J. W. Rayner: Nonstationary Signal Classification using Support Vector Machines. 11th IEEE Workshop on Statistical Signal Processing, 305--308, IEEE Signal Processing Society, Piscataway, NY (2001)
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Gretton, A., A. Doucet, R. Herbrich, P. Rayner and B. Schölkopf: Support Vector Regression for Black-Box System Identification. 11th IEEE Workshop on Statistical Signal Processing, 341--344, IEEE Signal Processing Society, Piscataway, NY (2001)
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Book Chapters (2)
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Gretton, A., A. J. Smola, J. Huang, M. Schmittfull, K. M. Borgwardt and B. Schölkopf: Covariate Shift by Kernel Mean Matching. Dataset Shift in Machine Learning, 131-160. (Eds.) Quiñonero Candela, J., M. Sugiyama, A. Schwaighofer, N. D. Lawrence, MIT Press, Cambridge, MA, USA (02 2009)
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Jegelka, S. and A. Gretton: Brisk Kernel ICA. Large Scale Kernel Machines, 225-250. (Eds.) Bottou, L., O. Chapelle, D. DeCoste, J. Weston, MIT Press, Cambridge, MA, USA (09 2007)
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MPI-Technical Reports (7)
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Gretton, A. and L. Györfi: Consistent Nonparametric Tests of Independence. (172) (07 2009)
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Blaschko, M. B. and A. Gretton: Taxonomy Inference Using Kernel Dependence Measures. (181) (11 2008)
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Gretton, A., K. Borgwardt, M. Rasch, B. Schölkopf and A. Smola: A Kernel Method for the Two-sample Problem. (157) (04 2008)
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Gretton, A., O. Bousquet, A. J. Smola and B. Schölkopf: Measuring Statistical Dependence with Hilbert-Schmidt Norms. MPI Technical Report (140), Max Planck Institute for Biological Cybernetics, Tübingen, Germany (06 2005)
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Bakir, G.H., A. Gretton, M.O. Franz and B. Schölkopf: Multivariate Regression with Stiefel Constraints. MPI Technical Report (128), Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2004)
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Gretton, A., A. Smola, O. Bousquet, R. Herbrich, B. Schölkopf and N.K. Logothetis: Behaviour and Convergence of the Constrained Covariance. MPI Technical Report (130), Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2004)
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Zhou, D., J. Weston, A. Gretton, O. Bousquet and B. Schölkopf: Ranking on Data Manifolds. MPI Technical Report (113), Max Planck Institute for Biological Cybernetics, Tübingen, Germany (June 2003)
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Technical Reports (5)
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Shen, H., S. Jegelka and A. Gretton: Geometric Analysis of Hilbert Schmidt Independence criterion based ICA contrast function. Technical report No.(PA006080) (10 2006)
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Kenji Fukumizu, Francis Bach and A. Gretton: Consistency of Kernel Canonical Correlation Analysis. Technical report No.(942) (June 2005)
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Gretton, A., Herbrich and Smola: The Kernel Mutual Information. Technical report (04 2003)
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Gretton, A., R. Herbrich, B. Schölkopf, A.J. Smola and P.J.W. Rayner: Bound on the Leave-One-Out Error for Density Support Estimation using $nu$-{SVM}s. Technical report (2001)
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Gretton, A., R. Herbrich, B. Schölkopf and P.J.W. Rayner: Bound on the Leave-One-Out Error for 2-Class Classification using $nu$-{SVM}s. Technical report (2001) [Note: Updated May 2003 (literature review expanded)]
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Abstracts (3)
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Ku, S.-P., A. Gretton, J. Macke, A. T. Tolias and N. K. Logothetis: Analysis of Pattern Recognition Methods in Classifying Bold Signals in Monkeys at 7-Tesla. AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles 2, 67 (06 2008)
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Belitski, A., A. Gretton, C. Magri, Y. Murayama, M. Montemurro, N. K. Logothetis and S. Panzeri: A time/frequency decomposition of information transmission by LFPs and spikes in the primary visual cortex. 37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007) 37, 1 (11 2007)
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Smola, A. J., A. Gretton, L. Song and B. Schölkopf: A Hilbert Space Embedding for Distributions. Proceedings of the 10th International Conference on Discovery Science (DS 2007) 10, 40-41 (10 2007)
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PhD Theses (1)
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Arthur Gretton: Kernel Methods for Classification and Signal Separation. 226, University of Cambridge, Cambridge (not published) (April 2003)
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Talks (5)
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Gretton, A. and L. Györfi: Nonparametric Indepedence Tests: Space Partitioning and Kernel Approaches. 19th International Conference on Algorithmic Learning Theory (ALT08), Budapest, Hungary (10 2008)
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Fukumizu, K., A. Gretton and A. Smola: Painless Embeddings of Distributions: the Function Space View (Part 1), 25th International Conference on Machine Learning (ICML 2008), Helsinki, Finland (07 2008)
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Gretton, A.: Hilbert Space Representations of Probability Distributions. 2nd Workshop on Machine Learning and Optimization at the ISM, Tokyo, Japan (10 2007)
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Gretton, A., K. Borgwardt, M. Rasch, B. Schölkopf and A. Smola: A Kernel Method for the Two-Sample-Problem. Twentieth Annual Conference on Neural Information Processing Systems : NIPS 2006, Vancouver, Canada (12 2006)
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Gretton, A., A. Smola, O. Bousquet, R. Herbrich, A. Belitski, M. Augath, Y. Murayama, B. Schölkopf and N. K. Logothetis: Kernel Constrained Covariance for Dependence Measurement. AISTATS 2005 (01 2005)
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