Blaschko, M., Gretton, A.
A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery
In MLG 2008, pages: 1-3, 6th International Workshop on Mining and Learning with Graphs, July 2008 (inproceedings)
Ku, S., Gretton, A., Macke, J., Tolias, A., Logothetis, N.
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, pages: 67, June 2008 (poster)
Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.
A Kernel Method for the Two-sample Problem
(157), Max-Planck-Institute for Biological Cybernetics Tübingen, April 2008 (techreport)
Rasch, M., Gretton, A., Murayama, Y., Maass, W., Logothetis, N.
Inferring Spike Trains From Local Field Potentials
Journal of Neurophysiology, 99(3):1461-1476, March 2008 (article)
Belitski, A., Gretton, A., Magri, C., Murayama, Y., Montemurro, M., Logothetis, N., Panzeri, S.
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, pages: 1, November 2007 (poster)
Gretton, A.
Hilbert Space Representations of Probability Distributions
2nd Workshop on Machine Learning and Optimization at the ISM, October 2007 (talk)
Smola, A., Gretton, A., Song, L., Schölkopf, B.
A Hilbert Space Embedding for Distributions
Proceedings of the 10th International Conference on Discovery Science (DS 2007), 10, pages: 40-41, October 2007 (poster)
Smola, A., Gretton, A., Song, L., Schölkopf, B.
A Hilbert Space Embedding for Distributions
In Algorithmic Learning Theory, Lecture Notes in Computer Science 4754 , pages: 13-31, (Editors: M Hutter and RA Servedio and E Takimoto), Springer, Berlin, Germany, 18th International Conference on Algorithmic Learning Theory (ALT), October 2007 (inproceedings)
Jegelka, S., Gretton, A.
Brisk Kernel ICA
In Large Scale Kernel Machines, pages: 225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)
Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.
A Kernel Method for the Two-Sample-Problem
In Advances in Neural Information Processing Systems 19, pages: 513-520, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)
Huang, J., Smola, A., Gretton, A., Borgwardt, K., Schölkopf, B.
Correcting Sample Selection Bias by Unlabeled Data
In Advances in Neural Information Processing Systems 19, pages: 601-608, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)
Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.
A Kernel Approach to Comparing Distributions
In Proceedings of the 22. AAAI Conference on Artificial Intelligence, pages: 1637-1641, AAAI Press, Menlo Park, CA, USA, Twenty-Second AAAI Conference on Artificial Intelligence (AAAI), July 2007 (inproceedings)
Song, L., Bedo, J., Borgwardt, K., Gretton, A., Smola, A.
Gene selection via the BAHSIC family of algorithms
Bioinformatics, 23(13: ISMB/ECCB 2007 Conference Proceedings):i490-i498, July 2007 (article)
Song, L., Smola, A., Gretton, A., Borgwardt, K., Bedo, J.
Supervised Feature Selection via Dependence Estimation
In Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), pages: 823-830, (Editors: Ghahramani, Z. ), ACM Press, New York, NY, USA, Twenty-Fourth Annual International Conference on Machine Learning (ICML), June 2007 (inproceedings)
Song, L., Smola, A., Gretton, A., Borgwardt, K.
A Dependence Maximization View of Clustering
In Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), pages: 815-822, (Editors: Ghahramani, Z. ), ACM Press, New York, NY, USA, Twenty-Fourth Annual International Conference on Machine Learning (ICML), June 2007 (inproceedings)
Shen, H., Jegelka, S., Gretton, A.
Fast Kernel ICA using an Approximate Newton Method
In JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007, pages: 476-483, (Editors: Meila, M. , X. Shen), MIT Press, Cambridge, MA, USA, 11th International Conference on Artificial Intelligence and Statistics, March 2007 (inproceedings)
Fukumizu, K., Bach, F., Gretton, A.
Statistical Consistency of Kernel Canonical Correlation Analysis
Journal of Machine Learning Research, 8, pages: 361-383, February 2007 (article)
Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.
A Kernel Method for the Two-Sample-Problem
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)
Shen, H., Jegelka, S., Gretton, A.
Geometric Analysis of Hilbert Schmidt Independence criterion based ICA contrast function
(PA006080), National ICT Australia, Canberra, Australia, October 2006 (techreport)
Davy, M., Desobry, F., Gretton, A., Doncarli, C.
An Online Support Vector Machine for Abnormal Events Detection
Signal Processing, 86(8):2009-2025, August 2006 (article)
Borgwardt, K., Gretton, A., Rasch, M., Kriegel, H., Schölkopf, B., Smola, A.
Integrating Structured Biological data by Kernel Maximum Mean Discrepancy
Bioinformatics, 22(4: ISMB 2006 Conference Proceedings):e49-e57, August 2006 (article)
Fukumizu, K., Bach, F., Gretton, A.
Statistical Convergence of Kernel CCA
In Advances in neural information processing systems 18, pages: 387-394, (Editors: Weiss, Y. , B. Schölkopf, J. Platt), MIT Press, Cambridge, MA, USA, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS), May 2006 (inproceedings)
Gretton, A., Belitski, A., Murayama, Y., Schölkopf, B., Logothetis, N.
The Effect of Artifacts on Dependence Measurement in fMRI
Magnetic Resonance Imaging, 24(4):401-409, April 2006 (article)
Jegelka, S., Gretton, A., Achlioptas, D.
Kernel ICA for Large Scale Problems
In pages: -, NIPS Workshop on Large Scale Kernel Machines, December 2005 (inproceedings)
Gretton, A., Herbrich, R., Smola, A., Bousquet, O., Schölkopf, B.
Kernel Methods for Measuring Independence
Journal of Machine Learning Research, 6, pages: 2075-2129, December 2005 (article)
Gretton, A., Belitski, A., Murayama, Y., Schölkopf, B., Logothetis, N.
Kernel methods for dependence testing in LFP-MUA
35(689.17), 35th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2005 (poster)
Gretton, A., Bousquet, O., Smola, A., Schoelkopf, B.
Measuring Statistical Dependence with Hilbert-Schmidt Norms
In Algorithmic Learning Theory, Lecture Notes in Computer Science, Vol. 3734, pages: 63-78, (Editors: S Jain and H-U Simon and E Tomita), Springer, Berlin, Germany, 16th International Conference ALT, October 2005 (inproceedings)
Gretton, A., Bousquet, O., Smola, A., Schölkopf, B.
Measuring Statistical Dependence with Hilbert-Schmidt Norms
(140), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2005 (techreport)
Fukumizu, K., Bach, F., Gretton, A.
Consistency of Kernel Canonical Correlation Analysis
(942), Institute of Statistical Mathematics, 4-6-7 Minami-azabu, Minato-ku, Tokyo 106-8569 Japan, June 2005 (techreport)
Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Belitski, A., Augath, M., Murayama, Y., Pauls, J., Schölkopf, B., Logothetis, N.
Kernel Constrained Covariance for Dependence Measurement
In Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics, pages: 112-119, (Editors: R Cowell, R and Z Ghahramani), AISTATS, January 2005 (inproceedings)
Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Belitski, A., Augath, M., Murayama, Y., Schölkopf, B., Logothetis, N.
Kernel Constrained Covariance for Dependence Measurement
AISTATS, January 2005 (talk)
Zhou, D., Weston, J., Gretton, A., Bousquet, O., Schölkopf, B.
Ranking on Data Manifolds
In Advances in neural information processing systems 16, pages: 169-176, (Editors: S Thrun and L Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)
Bakir, G., Gretton, A., Franz, M., Schölkopf, B.
Multivariate Regression with Stiefel Constraints
(128), MPI for Biological Cybernetics, Spemannstr 38, 72076, Tuebingen, 2004 (techreport)
BakIr, G., Gretton, A., Franz, M., Schölkopf, B.
Multivariate Regression via Stiefel Manifold Constraints
In Lecture Notes in Computer Science, Vol. 3175, pages: 262-269, (Editors: CE Rasmussen and HH Bülthoff and B Schölkopf and MA Giese), Springer, Berlin, Germany, Pattern Recognition, Proceedings of the 26th DAGM Symposium, 2004 (inproceedings)
Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Schölkopf, B., Logothetis, N.
Behaviour and Convergence of the Constrained Covariance
(130), MPI for Biological Cybernetics, 2004 (techreport)
Zhou, D., Weston, J., Gretton, A., Bousquet, O., Schölkopf, B.
Ranking on Data Manifolds
(113), Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany, June 2003 (techreport)
Gretton, A.
Kernel Methods for Classification and Signal Separation
pages: 226, Biologische Kybernetik, University of Cambridge, Cambridge, April 2003 (phdthesis)
Gretton, A., Desobry, ..
On-Line One-Class Support Vector Machines. An Application to Signal Segmentation
In IEEE ICASSP Vol. 2, pages: 709-712, IEEE ICASSP, April 2003 (inproceedings)
Gretton, A., Herbrich, R., Smola, A.
The Kernel Mutual Information
Max Planck Institute for Biological Cybernetics, April 2003 (techreport)
Gretton, A., Herbrich, R., Smola, A.
The Kernel Mutual Information
In IEEE ICASSP Vol. 4, pages: 880-883, IEEE ICASSP, April 2003 (inproceedings)
Davy, M., Gretton, A., Doucet, A., Rayner, P.
Optimized Support Vector Machines for Nonstationary Signal Classification
IEEE Signal Processing Letters, 9(12):442-445, December 2002 (article)
Gretton, A., Davy, M., Doucet, A., Rayner, P.
Nonstationary Signal Classification using Support Vector Machines
In 11th IEEE Workshop on Statistical Signal Processing, pages: 305-305, 11th IEEE Workshop on Statistical Signal Processing, 2001 (inproceedings)
Gretton, A., Herbrich, R., Schölkopf, B., Smola, A., Rayner, P.
Bound on the Leave-One-Out Error for Density Support Estimation using nu-SVMs
University of Cambridge, 2001 (techreport)
Gretton, A., Doucet, A., Herbrich, R., Rayner, P., Schölkopf, B.
Support Vector Regression for Black-Box System Identification
In 11th IEEE Workshop on Statistical Signal Processing, pages: 341-344, IEEE Signal Processing Society, Piscataway, NY, USA, 11th IEEE Workshop on Statistical Signal Processing, 2001 (inproceedings)
Gretton, A., Herbrich, R., Schölkopf, B., Rayner, P.
Bound on the Leave-One-Out Error for 2-Class Classification using nu-SVMs
University of Cambridge, 2001, Updated May 2003 (literature review expanded) (techreport)