Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

22 January 2018

Papers citing "Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms"

7 / 7 papers shown

Title
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory Guhan Chen Yicheng Li Qian Lin AAML 38 1 0 08 Oct 2024
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 57 0 0 24 Aug 2024
Spectral Algorithms on Manifolds through Diffusion Weichun Xia Lei Shi 16 1 0 06 Mar 2024
On the Optimality of Misspecified Spectral Algorithms Hao Zhang Yicheng Li Qian Lin 18 15 0 27 Mar 2023
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression Jiading Liu Lei Shi 30 9 0 20 Nov 2022
Sobolev Norm Learning Rates for Conditional Mean Embeddings Prem M. Talwai A. Shameli D. Simchi-Levi 24 10 0 16 May 2021
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm Simon Fischer Ingo Steinwart 15 148 0 23 Feb 2017