Kernel Methods

Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces NeurIPS 2022 Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data ICML 2022 Fast Graph Neural Tangent Kernel via Kronecker Sketching AAAI 2022 Feature Kernel Distillation ICLR 2022 Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion NeurIPS 2022 Forward Operator Estimation in Generative Models with Kernel Transfer Operators ICML 2022 Functional Output Regression with Infimal Convolution: Exploring the Huber and $ε$-insensitive Losses ICML 2022 Gauss-Legendre Features for Gaussian Process Regression JMLR 2022 Generalized Kernel Thinning ICLR 2022 Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more ICML 2022 Giga-scale Kernel Matrix-Vector Multiplication on GPU NeurIPS 2022 Graph Filtration Kernels AAAI 2022 GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NeurIPS 2022 Handling Hard Affine SDP Shape Constraints in RKHSs JMLR 2022 How Good Are Low-Rank Approximations in Gaussian Process Regression? AAAI 2022 Hypergraph Modeling via Spectral Embedding Connection: Hypergraph Cut, Weighted Kernel k-Means, and Heat Kernel AAAI 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022 KerGNNs: Interpretable Graph Neural Networks with Graph Kernels AAAI 2022 Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022 Kernel interpolation in Sobolev spaces is not consistent in low dimensions COLT 2022 Kernel Interpolation with Sparse Grids NeurIPS 2022 Kernelized Few-Shot Object Detection With Efficient Integral Aggregation CVPR 2022 Kernelized multi-graph matching ACML 2022 Kernel Methods for Radial Transformed Compositional Data with Many Zeros ICML 2022 Kernel Multimodal Continuous Attention NeurIPS 2022