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Kernel Methods

571 directly classified papers

Papers per year

Papers

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case JMLR 2024
Provable and Efficient Dataset Distillation for Kernel Ridge Regression NIPS 2024
Temporal Graph Neural Tangent Kernel with Graphon-Guaranteed NIPS 2024
The Nyström method for convex loss functions JMLR 2024
On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint) IJCAI 2024
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification AAAI 2024
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm JMLR 2024
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024
On the Optimality of Misspecified Spectral Algorithms JMLR 2024
Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces JMLR 2024
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels AISTATS 2024
A General Framework for the Analysis of Kernel-based Tests JMLR 2024
Efficient Convex Algorithms for Universal Kernel Learning JMLR 2024
On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity NIPS 2024
A Kernel Perspective on Distillation-based Collaborative Learning NIPS 2024
Inverse M-Kernels for Linear Universal Approximators of Non-Negative Functions NIPS 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression AISTATS 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NIPS 2024
Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features NIPS 2024
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression NIPS 2024
Dense Associative Memory Through the Lens of Random Features NIPS 2024
Infinite-Dimensional Feature Interaction NIPS 2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NIPS 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality NIPS 2024
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models AISTATS 2024