Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression

20 November 2022

Papers citing "Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression"

9 / 9 papers shown

Title
Convergence Analysis of regularised Nyström method for Functional Linear Regression Naveen Gupta Sivananthan Sampath 32 0 0 25 Oct 2024
Distributed Learning with Discretely Observed Functional Data Jiading Liu Lei Shi 15 0 0 03 Oct 2024
Spectral Algorithms on Manifolds through Diffusion Weichun Xia Lei Shi 16 1 0 06 Mar 2024
On regularized polynomial functional regression Markus Holzleitner S. Pereverzyev 24 6 0 06 Nov 2023
Distributed Gradient Descent for Functional Learning Zhan Yu Jun Fan Zhongjie Shi Ding-Xuan Zhou 21 1 0 12 May 2023
On the Optimality of Misspecified Kernel Ridge Regression Haobo Zhang Yicheng Li Weihao Lu Qian Lin 42 12 0 12 May 2023
On the Optimality of Misspecified Spectral Algorithms Hao Zhang Yicheng Li Qian Lin 18 15 0 27 Mar 2023
Capacity dependent analysis for functional online learning algorithms Xin Guo Zheng-Chu Guo Lei Shi 32 20 0 25 Sep 2022
A reproducing kernel Hilbert space approach to functional linear regression M. Yuan Tommaso Cai 95 278 0 12 Nov 2012