reproducing kernel hilbert space

Nonparametric Sparsity and Regularization JMLR 2013 q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions NeurIPS 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 A Kernel Two-Sample Test JMLR 2012 Learning from Distributions via Support Measure Machines NeurIPS 2012 Linear Regression With Random Projections JMLR 2012 Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming JMLR 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Refinement of Operator-valued Reproducing Kernels JMLR 2012 Convergence Rates of Efficient Global Optimization Algorithms JMLR 2011 Generalizing from Several Related Classification Tasks to a New Unlabeled Sample NeurIPS 2011 Kernel Bayes' Rule NeurIPS 2011 Kernel Belief Propagation AISTATS 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels NeurIPS 2011 Semi-supervised Learning by Higher Order Regularization AISTATS 2011 Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NeurIPS 2011 Universality, Characteristic Kernels and RKHS Embedding of Measures JMLR 2011 Graph Kernels JMLR 2010 Hilbert Space Embeddings and Metrics on Probability Measures JMLR 2010 Kernel Partial Least Squares is Universally Consistent AISTATS 2010 Nonlinear functional regression: a functional RKHS approach AISTATS 2010 On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010