Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$ - and $O(1/n^2)$ -type of Risk Bounds

7 February 2017

Papers citing "Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds"

9 / 9 papers shown

Title
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 89 2 0 09 Jan 2023
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 105 13 0 19 Jul 2021
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning Blake E. Woodworth Nathan Srebro 64 22 0 04 Jun 2021
Why Does Multi-Epoch Training Help? Yi Tian Xu Qi Qian Hao Li Rong Jin 62 1 0 13 May 2021
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ Yegor Klochkov Nikita Zhivotovskiy 81 62 0 22 Mar 2021
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory Yunbei Xu A. Zeevi 130 17 0 12 Nov 2020
$A generalized Catoni's ${\rm M}$-estimator under finite {$α$-th moment assumption} with $α\in (1,2)$$ A generalized Catoni's ${\rm M}$ -estimator under finite { $α$ -th moment assumption} with $α\in (1,2)$ Peng Chen Xinghu Jin Xiang Li Lihu Xu 65 25 0 10 Oct 2020
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time Y. Lee Zhao Song Qiuyi Zhang 110 117 0 11 May 2019
$$\ell_1$-regression with Heavy-tailed Distributions$ $\ell_1$ -regression with Heavy-tailed Distributions Lijun Zhang Zhi Zhou 38 3 0 02 May 2018