Composite kernel learning
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[1] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[2] Yves Grandvalet,et al. More efficiency in multiple kernel learning , 2007, ICML '07.
[3] Sayan Mukherjee,et al. Feature Selection for SVMs , 2000, NIPS.
[4] Klaus-Robert Müller,et al. The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials , 2004, IEEE Transactions on Biomedical Engineering.
[5] Alain Rakotomamonjy,et al. BCI Competition III: Dataset II- Ensemble of SVMs for BCI P300 Speller , 2008, IEEE Transactions on Biomedical Engineering.
[6] Pierre Morizet-Mahoudeaux,et al. Hierarchical Penalization , 2007, NIPS.
[7] Massimiliano Pontil,et al. Convex multi-task feature learning , 2008, Machine Learning.
[8] Alexander J. Smola,et al. Learning the Kernel with Hyperkernels , 2005, J. Mach. Learn. Res..
[9] Bruno Torrésani,et al. Sparsity and persistence: mixed norms provide simple signal models with dependent coefficients , 2009, Signal Image Video Process..
[10] Mila Nikolova,et al. Local Strong Homogeneity of a Regularized Estimator , 2000, SIAM J. Appl. Math..
[11] Yves Grandvalet,et al. Outcomes of the Equivalence of Adaptive Ridge with Least Absolute Shrinkage , 1998, NIPS.
[12] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[13] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[14] Alexander J. Smola,et al. Learning with Kernels: support vector machines, regularization, optimization, and beyond , 2001, Adaptive computation and machine learning series.
[15] Alexander Shapiro,et al. Optimization Problems with Perturbations: A Guided Tour , 1998, SIAM Rev..
[16] Michael I. Jordan,et al. Multiple kernel learning, conic duality, and the SMO algorithm , 2004, ICML.
[17] L. Breiman. Heuristics of instability and stabilization in model selection , 1996 .
[18] Francis R. Bach,et al. Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning , 2008, NIPS.
[19] Nello Cristianini,et al. Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..
[20] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[21] Bernhard Schölkopf,et al. Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces , 2005, EURASIP J. Adv. Signal Process..
[22] Alain Rakotomamonjy,et al. Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances , 2005, ICANN.
[23] Yoshua Bengio,et al. No Unbiased Estimator of the Variance of K-Fold Cross-Validation , 2003, J. Mach. Learn. Res..
[24] Yves Grandvalet,et al. Adaptive Scaling for Feature Selection in SVMs , 2002, NIPS.
[25] Charles A. Micchelli,et al. A DC-programming algorithm for kernel selection , 2006, ICML.
[26] Gunnar Rätsch,et al. Large Scale Multiple Kernel Learning , 2006, J. Mach. Learn. Res..
[27] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[28] E. Donchin,et al. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.
[29] P. Zhao,et al. The composite absolute penalties family for grouped and hierarchical variable selection , 2009, 0909.0411.
[30] André Elisseeff,et al. Stability and Generalization , 2002, J. Mach. Learn. Res..
[31] Olivier Bousquet,et al. On the Complexity of Learning the Kernel Matrix , 2002, NIPS.
[32] N. Cristianini,et al. On Kernel-Target Alignment , 2001, NIPS.
[33] Zenglin Xu,et al. An Extended Level Method for Efficient Multiple Kernel Learning , 2008, NIPS.
[34] Ricardo Chavarriaga,et al. Fast Recognition of Anticipation-Related Potentials , 2009, IEEE Transactions on Biomedical Engineering.
[35] Nello Cristianini,et al. Dynamically Adapting Kernels in Support Vector Machines , 1998, NIPS.
[36] Shai Ben-David,et al. Learning Bounds for Support Vector Machines with Learned Kernels , 2006, COLT.
[37] W. Walter,et al. Contingent Negative Variation : An Electric Sign of Sensori-Motor Association and Expectancy in the Human Brain , 1964, Nature.
[38] Sayan Mukherjee,et al. Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.