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kernel ridge regression

111 papers

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Also known as

KRR

Co-occurring keywords

kernel methods (1097) reproducing kernel hilbert space (334) generalization error (285) distributed learning (563) gaussian process (1200) gradient descent (1144) kernel approximation (100) nystrom method (46) convergence rate (607) minimax optimality (76)

Papers

Provably Strict Generalisation Benefit for Invariance in Kernel Methods NIPS 2021
Distributed Nyström Kernel Learning with Communications ICML 2021
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime NIPS 2021
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions NIPS 2021
Fast Rates for Structured Prediction COLT 2021
How rotational invariance of common kernels prevents generalization in high dimensions ICML 2021
Kernel regression in high dimensions: Refined analysis beyond double descent AISTATS 2021
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression AISTATS 2021
Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression AISTATS 2021
Generalization Properties of hyper-RKHS and its Applications JMLR 2021
Demystifying Orthogonal Monte Carlo and Beyond NIPS 2020
Data-driven confidence bands for distributed nonparametric regression COLT 2020
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing AISTATS 2020
Implicit Regularization of Random Feature Models ICML 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
Near Input Sparsity Time Kernel Embeddings via Adaptive Sampling ICML 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020
Distributed Kernel Ridge Regression with Communications JMLR 2020
Conjugate Gradients for Kernel Machines JMLR 2020
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling AAAI 2020
Reducing training time by efficient localized kernel regression AISTATS 2019
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping JMLR 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit COLT 2019
On Kernel Derivative Approximation with Random Fourier Features AISTATS 2019
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NIPS 2019