kernel ridge regression

Provably Strict Generalisation Benefit for Invariance in Kernel Methods NeurIPS 2021 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network AISTATS 2021 Stochastic Gradient Descent Meets Distribution Regression AISTATS 2021 Conjugate Gradients for Kernel Machines JMLR 2020 Data-driven confidence bands for distributed nonparametric regression COLT 2020 Demystifying Orthogonal Monte Carlo and Beyond NeurIPS 2020 Distributed Kernel Ridge Regression with Communications JMLR 2020 Implicit Regularization of Random Feature Models ICML 2020 Kernel Alignment Risk Estimator: Risk Prediction from Training Data NeurIPS 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 Random Fourier Features via Fast Surrogate Leverage Weighted Sampling AAAI 2020 Scaling up Kernel Ridge Regression via Locality Sensitive Hashing AISTATS 2020 Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping JMLR 2019 Efficient online learning with kernels for adversarial large scale problems NeurIPS 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NeurIPS 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 Reducing training time by efficient localized kernel regression AISTATS 2019 Sharp Theoretical Analysis for Nonparametric Testing under Random Projection COLT 2019 Sublinear quantum algorithms for training linear and kernel-based classifiers ICML 2019 Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel k-means Clustering ICML 2019 Initialization matters: Orthogonal Predictive State Recurrent Neural Networks ICLR 2018 On Fast Leverage Score Sampling and Optimal Learning NeurIPS 2018 Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data ICML 2018