reproducing kernel hilbert space

Parallelizing Spectrally Regularized Kernel Algorithms JMLR 2018 Streaming kernel regression with provably adaptive mean, variance, and regularization JMLR 2018 A Covariance Matrix Adaptation Evolution Strategy for Direct Policy Search in Reproducing Kernel Hilbert Space ACML 2017 A Framework for Optimal Matching for Causal Inference AISTATS 2017 Density Estimation in Infinite Dimensional Exponential Families JMLR 2017 Distributed Learning with Regularized Least Squares JMLR 2017 Fast Bayesian Intensity Estimation for the Permanental Process ICML 2017 Invariance and Stability of Deep Convolutional Representations NeurIPS 2017 Linearly constrained Gaussian processes NeurIPS 2017 Minimax Estimation of Kernel Mean Embeddings JMLR 2017 On Kernelized Multi-armed Bandits ICML 2017 Online Learning for Multivariate Hawkes Processes NeurIPS 2017 Poisson intensity estimation with reproducing kernels AISTATS 2017 Relative Error Embeddings of the Gaussian Kernel Distance ALT 2017 Robust Hypothesis Test for Nonlinear Effect with Gaussian Processes NeurIPS 2017 Variational Inference for Gaussian Process Models with Linear Complexity NeurIPS 2017 A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016 A Kernel Test of Goodness of Fit ICML 2016 A Unifying Framework in Vector-valued Reproducing Kernel Hilbert Spaces for Manifold Regularization and Co-Regularized Multi-view Learning JMLR 2016 Back to the Future: Radial Basis Function Networks Revisited AISTATS 2016 Convergence guarantees for kernel-based quadrature rules in misspecified settings NeurIPS 2016 Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis NeurIPS 2016 End-to-End Kernel Learning with Supervised Convolutional Kernel Networks NeurIPS 2016 Error Analysis of Generalized Nyström Kernel Regression NeurIPS 2016 Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces RSS 2016