Kernel Methods

Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee JMLR 2024 Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed NeurIPS 2024 The Nyström method for convex loss functions JMLR 2024 Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024 Treatment Effects Estimation By Uniform Transformer ICLR 2024 Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024 Uncertainty Estimation with Recursive Feature Machines UAI 2024 Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification AAAI 2024 A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing COLT 2023 A Lower Bound for Linear and Kernel Regression with Adaptive Covariates COLT 2023 A Statistical Perspective on Retrieval-Based Models ICML 2023 Can Infinitely Wide Deep Nets Help Small-data Multi-label Learning? ACML 2023 Collaborative Pure Exploration in Kernel Bandit ICLR 2023 Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel AISTATS 2023 Consistency of Multiple Kernel Clustering ICML 2023 CosNet: A Generalized Spectral Kernel Network NeurIPS 2023 Deep Kernel Regression with Finite Learnable Kernels ACML 2023 Deep learning with kernels through RKHM and the Perron-Frobenius operator NeurIPS 2023 Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel NeurIPS 2023 Efficient Structure-preserving Support Tensor Train Machine JMLR 2023 Error Estimation for Random Fourier Features AISTATS 2023 Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms ICML 2023 GEQ: Gaussian Kernel Inspired Equilibrium Models NeurIPS 2023 GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-Shot Class Incremental Task CVPR 2023 Gradient Boosting Performs Gaussian Process Inference ICLR 2023