reproducing kernel hilbert space

Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration AAAI 2024 Scalable Kernel Inverse Optimization NeurIPS 2024 Spectral Analysis of the Neural Tangent Kernel for Deep Residual Networks JMLR 2024 Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024 Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024 Active Cost-aware Labeling of Streaming Data AISTATS 2023 Adaptation to Misspecified Kernel Regularity in Kernelised Bandits AISTATS 2023 Adaptive Learning of Density Ratios in RKHS JMLR 2023 A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points JMLR 2023 Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Spaces AAAI 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Functional Renyi Differential Privacy for Generative Modeling NeurIPS 2023 Hierarchical Kernels in Deep Kernel Learning JMLR 2023 Interpolating Classifiers Make Few Mistakes JMLR 2023 Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches JMLR 2023 Kernelized Diffusion Maps COLT 2023 Kernel Quadrature with Randomly Pivoted Cholesky NeurIPS 2023 Learning in RKHM: a C*-Algebraic Twist for Kernel Machines AISTATS 2023 Learning Kernelized Contextual Bandits in a Distributed and Asynchronous Environment ICLR 2023 Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023 Mean Parity Fair Regression in RKHS AISTATS 2023 Metrizing Weak Convergence with Maximum Mean Discrepancies JMLR 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training ICLR 2023 Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces ICML 2023 On Distance and Kernel Measures of Conditional Dependence JMLR 2023