Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model

15 June 2020

Papers citing "Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model"

9 / 9 papers shown

Title
Corner Gradient Descent Dmitry Yarotsky 46 0 0 16 Apr 2025
Better Rates for Random Task Orderings in Continual Linear Models Itay Evron Ran Levinstein Matan Schliserman Uri Sherman Tomer Koren Daniel Soudry Nathan Srebro CLL 40 0 0 06 Apr 2025
Scaling Laws in Linear Regression: Compute, Parameters, and Data Licong Lin Jingfeng Wu Sham Kakade Peter L. Bartlett Jason D. Lee LRM 44 15 0 12 Jun 2024
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression Jiading Liu Lei Shi 33 9 0 20 Nov 2022
Non-reversible Parallel Tempering for Deep Posterior Approximation Wei Deng Qian Zhang Qi Feng F. Liang Guang Lin 31 4 0 20 Nov 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD Yu Huang Yingbin Liang Longbo Huang MLT 30 8 0 18 Jun 2022
Polynomial convergence of iterations of certain random operators in Hilbert space Soumyadip Ghosh Ying-Ling Lu T. Nowicki 9 0 0 04 Feb 2022
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions Maksim Velikanov Dmitry Yarotsky 22 6 0 02 Feb 2022
Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves Rahul Singh Liyuan Xu Arthur Gretton OffRL 68 28 0 10 Oct 2020