conftrace_
← Core Methods
Machine Learning › Core Methods ›

Kernel Methods

642 papers

Papers per year

9
23
20
31
19
'05
'10
'15
'20
'25

Papers

Towards a Persistence Diagram that is Robust to Noise and Varied Densities ICML 2023
Efficient Structure-preserving Support Tensor Train Machine JMLR 2023
Graph-Aided Online Multi-Kernel Learning JMLR 2023
The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time JMLR 2023
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces JMLR 2023
Optimal Convergence Rates for Distributed Nystroem Approximation JMLR 2023
Minimax Risk Classifiers with 0-1 Loss JMLR 2023
Optimal Rates for Regularized Conditional Mean Embedding Learning NIPS 2022
GraphQNTK: Quantum Neural Tangent Kernel for Graph Data NIPS 2022
Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means NIPS 2022
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels NIPS 2022
Giga-scale Kernel Matrix-Vector Multiplication on GPU NIPS 2022
Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion NIPS 2022
Template based Graph Neural Network with Optimal Transport Distances NIPS 2022
SignRFF: Sign Random Fourier Features NIPS 2022
Kernel Multimodal Continuous Attention NIPS 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? NIPS 2022
Efficient Aggregated Kernel Tests using Incomplete $U$-statistics NIPS 2022
Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NIPS 2022
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces NIPS 2022
Target alignment in truncated kernel ridge regression NIPS 2022
Kernel Interpolation with Sparse Grids NIPS 2022
Learning with convolution and pooling operations in kernel methods NIPS 2022
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime NIPS 2022