Optimal learning rates for Kernel Conjugate Gradient regression

29 September 2010

Papers citing "Optimal learning rates for Kernel Conjugate Gradient regression"

20 / 20 papers shown

Title
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 148 1 0 24 Aug 2024
Early stopping by correlating online indicators in neural networks M. Ferro V. Darriba Francisco J. Ribadas Pena Jesús Vilares 48 9 0 04 Feb 2024
Capacity dependent analysis for functional online learning algorithms Xin Guo Zheng-Chu Guo Lei Shi 65 20 0 25 Sep 2022
Non-asymptotic Optimal Prediction Error for Growing-dimensional Partially Functional Linear Models Huiming Zhang Xiaoyu Lei 88 1 0 10 Sep 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 134 177 0 23 Apr 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 84 1 0 11 Dec 2019
KTBoost: Combined Kernel and Tree Boosting Fabio Sigrist 89 27 0 11 Feb 2019
Kernel Conjugate Gradient Methods with Random Projections Bailey Kacsmar Douglas R Stinson 61 4 0 05 Nov 2018
Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems Yang You J. Demmel Cho-Jui Hsieh R. Vuduc 58 33 0 01 May 2018
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network Zheng-Chu Guo Lei Shi Qiang Wu 47 43 0 07 Aug 2017
Kernel partial least squares for stationary data Marco Singer Tatyana Krivobokova Axel Munk 43 7 0 12 Jun 2017
Faster Kernel Ridge Regression Using Sketching and Preconditioning H. Avron K. Clarkson David P. Woodruff 127 125 0 10 Nov 2016
Distributed learning with regularized least squares Shaobo Lin Xin Guo Ding-Xuan Zhou 184 191 0 11 Aug 2016
Convergence rates of Kernel Conjugate Gradient for random design regression Gilles Blanchard Nicole E. Kramer 71 38 0 08 Jul 2016
Generalization Properties of Learning with Random Features Alessandro Rudi Lorenzo Rosasco MLT 102 331 0 14 Feb 2016
Partial least squares for dependent data Marco Singer Tatyana Krivobokova B. L. de Groot Axel Munk 59 16 0 16 Oct 2015
Iterative Regularization for Learning with Convex Loss Functions Junhong Lin Lorenzo Rosasco Ding-Xuan Zhou 92 43 0 31 Mar 2015
Learning with incremental iterative regularization Lorenzo Rosasco S. Villa 69 14 0 30 Apr 2014
Early stopping and non-parametric regression: An optimal data-dependent stopping rule Garvesh Raskutti Martin J. Wainwright Bin Yu 151 301 0 15 Jun 2013
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates Yuchen Zhang John C. Duchi Martin J. Wainwright 377 379 0 22 May 2013