Kernel Methods

Learning from End User Data with Shuffled Differential Privacy over Kernel Densities ICLR 2025 Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators AISTATS 2025 Metric Learning in an RKHS UAI 2025 Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning AISTATS 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 Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs AISTATS 2025 Representer Theorems for Metric and Preference Learning: Geometric Insights and Algorithms AISTATS 2025 Robust Kernel Hypothesis Testing under Data Corruption AISTATS 2025 Safe exploration in reproducing kernel Hilbert spaces AISTATS 2025 Sequential Kernelized Stein Discrepancy AISTATS 2025 Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes ICLR 2025 Skill Disentanglement in Reproducing Kernel Hilbert Space AAAI 2025 Statistical inference on black-box generative models in the data kernel perspective space ACL 2025 Tensor Network Based Feature Learning Model AISTATS 2025 Tensor Network-Constrained Kernel Machines as Gaussian Processes AISTATS 2025 The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs JMLR 2025 The Uniformly Rotated Mondrian Kernel AISTATS 2025 Tighter Confidence Bounds for Sequential Kernel Regression AISTATS 2025 Toward Interpretable Time Series Modeling: A Kernel Representation Perspective IJCAI 2025 Unsupervised Kernel-based Multi-view Feature Selection with Robust Self-representation and Binary Hashing AAAI 2025 Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation ICLR 2025 Variance-Aware Estimation of Kernel Mean Embedding JMLR 2025