reproducing kernel hilbert space

An analysis of Ermakov-Zolotukhin quadrature using kernels NeurIPS 2021 Application of kernel hypothesis testing on set-valued data UAI 2021 A Spectral Analysis of Dot-product Kernels AISTATS 2021 COKE: Communication-Censored Decentralized Kernel Learning JMLR 2021 Consistency of Gaussian Process Regression in Metric Spaces JMLR 2021 Counterfactual Mean Embeddings JMLR 2021 Deconditional Downscaling with Gaussian Processes NeurIPS 2021 Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS ICLR 2021 Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures AISTATS 2021 Framing RNN as a kernel method: A neural ODE approach NeurIPS 2021 Generalization Properties of hyper-RKHS and its Applications JMLR 2021 Generative Particle Variational Inference via Estimation of Functional Gradients ICML 2021 Gradient Descent in RKHS with Importance Labeling AISTATS 2021 Improved Mutual Information Estimation AAAI 2021 KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support NeurIPS 2021 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation AISTATS 2021 Kernel Thinning COLT 2021 Last iterate convergence of SGD for Least-Squares in the Interpolation regime. NeurIPS 2021 Learning Approximate Forward Reachable Sets Using Separating Kernels L4DC 2021 Learning-Based Image Registration With Meta-Regularization CVPR 2021 Learning Strategies in Decentralized Matching Markets under Uncertain Preferences JMLR 2021 Misspecified Gaussian Process Bandit Optimization NeurIPS 2021 Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings AISTATS 2021 Nonlinear Data-Enabled Prediction and Control L4DC 2021 Nonlinear Functional Output Regression: A Dictionary Approach AISTATS 2021