reproducing kernel hilbert space

Metric Learning in an RKHS UAI 2025 Nonparametric estimation of Hawkes processes with RKHSs AISTATS 2025 Nyström Kernel Stein Discrepancy AISTATS 2025 On the Approximation of Kernel functions JMLR 2025 Optimal Functional Bilinear Regression with Two-dimensional Functional Covariates via Reproducing Kernel Hilbert Space JMLR 2025 ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models CVPR 2025 Reinforcement Learning for Infinite-Dimensional Systems JMLR 2025 Representer Theorems for Metric and Preference Learning: Geometric Insights and Algorithms AISTATS 2025 Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning ICLR 2025 Safe exploration in reproducing kernel Hilbert spaces AISTATS 2025 Skill Disentanglement in Reproducing Kernel Hilbert Space AAAI 2025 Step and Smooth Decompositions as Topological Clustering JMLR 2025 Towards Unified Native Spaces in Kernel Methods JMLR 2025 Variance-Aware Estimation of Kernel Mean Embedding JMLR 2025 A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators JMLR 2024 Adversarial Contextual Bandits Go Kernelized ALT 2024 A General Framework for the Analysis of Kernel-based Tests JMLR 2024 A multi-modal distributed learning algorithm in reproducing kernel Hilbert spaces L4DC 2024 An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression ICLR 2024 Analysis of Kernel Mirror Prox for Measure Optimization AISTATS 2024 Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data ICLR 2024 Causal Modeling with Stationary Diffusions AISTATS 2024 Correspondence-Free SE(3) Point Cloud Registration in RKHS via Unsupervised Equivariant Learning ECCV 2024 Debiased Collaborative Filtering with Kernel-Based Causal Balancing ICLR 2024 Deep Hierarchical Graph Alignment Kernels IJCAI 2024