Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
On the influence of the kernel on the consistency of support vector machines
The Journal of Machine Learning Research
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Multiple kernel learning, conic duality, and the SMO algorithm
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning the Kernel with Hyperkernels
The Journal of Machine Learning Research
Mercer theorem for RKHS on noncompact sets
Journal of Complexity
A DC-programming algorithm for kernel selection
ICML '06 Proceedings of the 23rd international conference on Machine learning
Feature space perspectives for learning the kernel
Machine Learning
Learning convex combinations of continuously parameterized basic kernels
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Spectral algorithms for supervised learning
Neural Computation
The Journal of Machine Learning Research
Fast kernel-based independent component analysis
IEEE Transactions on Signal Processing
Reproducing kernel banach spaces for machine learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Reproducing Kernel Banach Spaces for Machine Learning
The Journal of Machine Learning Research
Approximation of high-dimensional kernel matrices by multilevel circulant matrices
Journal of Complexity
Hilbert Space Embeddings and Metrics on Probability Measures
The Journal of Machine Learning Research
Radial kernels and their reproducing kernel Hilbert spaces
Journal of Complexity
Vector field learning via spectral filtering
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
A new scheme to learn a kernel in regularization networks
Neurocomputing
Universality, Characteristic Kernels and RKHS Embedding of Measures
The Journal of Machine Learning Research
Operators for transforming kernels into quasi-local kernels that improve SVM accuracy
Journal of Intelligent Information Systems
Refinement of operator-valued reproducing kernels
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Distributed parametric and nonparametric regression with on-line performance bounds computation
Automatica (Journal of IFAC)
Finite rank kernels for multi-task learning
Advances in Computational Mathematics
Multivariate approximation by translates of the Korobov function on Smolyak grids
Journal of Complexity
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In this paper we investigate conditions on the features of a continuous kernel so that it may approximate an arbitrary continuous target function uniformly on any compact subset of the input space. A number of concrete examples are given of kernels with this universal approximating property.