Stochastic Variance-Reduced Cubic Regularization for Nonconvex
Optimization

Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization

20 February 2018

Zhe Wang

Papers citing "Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization"

7 / 7 papers shown

Title
Second-Order Min-Max Optimization with Lazy Hessians Lesi Chen Chengchang Liu Jingzhao Zhang 46 1 0 12 Oct 2024
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods El Mahdi Chayti N. Doikov Martin Jaggi ODL 27 5 0 23 Feb 2023
Augmented Newton Method for Optimization: Global Linear Rate and Momentum Interpretation M. Morshed ODL 18 1 0 23 May 2022
Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence Sen Na Michal Derezinski Michael W. Mahoney 27 16 0 20 Apr 2022
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property Yi Zhou Zhe Wang Yingbin Liang 24 23 0 22 Aug 2018
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 84 736 0 19 Mar 2014