conftrace_

reproducing kernel hilbert space

334 papers

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Also known as

RKHS

Co-occurring keywords

kernel methods (1097) gaussian process (1200) maximum mean discrepancy (164) regret bound (1926) kernel ridge regression (111) support vector machine (978) convex optimization (1321) kernel mean embedding (43) generalization bound (652) bayesian optimization (624)

Papers

Detecting Unobserved Confounders: A Kernelized Regression Approach AAAI 2026
LUCID: Learning-Enabled Uncertainty-Aware Certification of Stochastic Dynamical Systems AAAI 2026
Adaptive Hyperbolic Kernels: Modulated Embedding in de Branges-Rovnyak Spaces AAAI 2026
Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint) AAAI 2026
Towards Unified Native Spaces in Kernel Methods JMLR 2025
Optimal Functional Bilinear Regression with Two-dimensional Functional Covariates via Reproducing Kernel Hilbert Space JMLR 2025
KP-PINNs: Kernel Packet Accelerated Physics Informed Neural Networks IJCAI 2025
Variance-Aware Estimation of Kernel Mean Embedding JMLR 2025
Reinforcement Learning for Infinite-Dimensional Systems JMLR 2025
On the Approximation of Kernel functions JMLR 2025
DeMo: Deep Motion Field Consensus with Learnable Kernels for Two-view Correspondence Learning AAAI 2025
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling JMLR 2025
ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models CVPR 2025
Step and Smooth Decompositions as Topological Clustering JMLR 2025
Learning causal graphs via nonlinear sufficient dimension reduction JMLR 2025
MDP3: A Training-free Approach for List-wise Frame Selection in Video-LLMs ICCV 2025
Skill Disentanglement in Reproducing Kernel Hilbert Space AAAI 2025
Error Bounds for Gaussian Process Regression Under Bounded Support Noise with Applications to Safety Certification AAAI 2025
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
Kernel Thinning JMLR 2024
On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint) IJCAI 2024
On the Optimality of Misspecified Spectral Algorithms JMLR 2024
Localisation of Regularised and Multiview Support Vector Machine Learning JMLR 2024
Analysis of Kernel Mirror Prox for Measure Optimization AISTATS 2024