kernel ridge regression

Parallelizing Spectrally Regularized Kernel Algorithms JMLR 2018 The Geometry of Random Features AISTATS 2018 UnibucKernel Reloaded: First Place in Arabic Dialect Identification for the Second Year in a Row COLING 2018 Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible ICML 2017 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017 Hypothesis Transfer Learning via Transformation Functions NeurIPS 2017 Memory Efficient Kernel Approximation JMLR 2017 Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees ICML 2017 Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016 Error Analysis of Generalized Nyström Kernel Regression NeurIPS 2016 Fast DPP Sampling for Nystrom with Application to Kernel Methods ICML 2016 Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching ICML 2016 Hyperparameter optimization with approximate gradient ICML 2016 Optimal Learning Rates for Localized SVMs JMLR 2016 Probabilistic Approximate Least-Squares AISTATS 2016 Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates JMLR 2015 Fast Randomized Kernel Ridge Regression with Statistical Guarantees NeurIPS 2015 Less is More: Nyström Computational Regularization NeurIPS 2015 Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule JMLR 2014 Fast Prediction for Large-Scale Kernel Machines NeurIPS 2014 Memory Efficient Kernel Approximation ICML 2014 Divide and Conquer Kernel Ridge Regression COLT 2013 Linear Regression With Random Projections JMLR 2012 Multiple Operator-valued Kernel Learning NeurIPS 2012 Multi-task Regression using Minimal Penalties JMLR 2012