conftrace_

reproducing kernel hilbert space

334 papers

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Also known as

RKHS

Co-occurring keywords

kernel methods (1097) gaussian process (1200) maximum mean discrepancy (164) regret bound (1926) kernel ridge regression (111) support vector machine (978) convex optimization (1321) kernel mean embedding (43) generalization bound (652) bayesian optimization (624)

Papers

Consistency of Robust Kernel Density Estimators COLT 2013
Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels JMLR 2013
Robust Estimation of Nonrigid Transformation for Point Set Registration CVPR 2013
Smooth Operators ICML 2013
Stability of Multi-Task Kernel Regression Algorithms ACML 2013
Optimal kernel choice for large-scale two-sample tests NIPS 2012
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming JMLR 2012
A Kernel Two-Sample Test JMLR 2012
Learning from Distributions via Support Measure Machines NIPS 2012
Linear Regression With Random Projections JMLR 2012
Refinement of Operator-valued Reproducing Kernels JMLR 2012
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample NIPS 2011
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NIPS 2011
Semi-supervised Learning by Higher Order Regularization AISTATS 2011
Convergence Rates of Efficient Global Optimization Algorithms JMLR 2011
Universality, Characteristic Kernels and RKHS Embedding of Measures JMLR 2011
Kernel Bayes' Rule NIPS 2011
Kernel Belief Propagation AISTATS 2011
Optimal learning rates for Kernel Conjugate Gradient regression NIPS 2010
Hilbert Space Embeddings and Metrics on Probability Measures JMLR 2010
Nonlinear functional regression: a functional RKHS approach AISTATS 2010
On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010
Kernel Partial Least Squares is Universally Consistent AISTATS 2010
Spectral Regularization for Support Estimation NIPS 2010
Graph Kernels JMLR 2010