reproducing kernel hilbert space

Gaussian process nonparametric tensor estimator and its minimax optimality ICML 2016 Incremental Variational Sparse Gaussian Process Regression NeurIPS 2016 Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels JMLR 2016 Iterative Regularization for Learning with Convex Loss Functions JMLR 2016 Joint quantile regression in vector-valued RKHSs NeurIPS 2016 K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016 Kernel Bayesian Inference with Posterior Regularization NeurIPS 2016 Kernel Mean Shrinkage Estimators JMLR 2016 Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds CVPR 2016 Learning Theory for Distribution Regression JMLR 2016 Localized Multiple Kernel Learning—A Convex Approach ACML 2016 Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels NeurIPS 2016 Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning NeurIPS 2016 Mixture Proportion Estimation via Kernel Embeddings of Distributions ICML 2016 Model-free Variable Selection in Reproducing Kernel Hilbert Space JMLR 2016 Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings AISTATS 2016 On Quantile Regression in Reproducing Kernel Hilbert Spaces with the Data Sparsity Constraint JMLR 2016 Operator-valued Kernels for Learning from Functional Response Data JMLR 2016 Random Fourier Features For Operator-Valued Kernels ACML 2016 Sparsity and Error Analysis of Empirical Feature-Based Regularization Schemes JMLR 2016 Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Synergy of Monotonic Rules JMLR 2016 Discrete Reproducing Kernel Hilbert Spaces: Sampling and Distribution of Dirac-masses JMLR 2015 Fast Two-Sample Testing with Analytic Representations of Probability Measures NeurIPS 2015 Learning Multiple Visual Tasks While Discovering Their Structure CVPR 2015