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Stochastic Variance Reduced Primal Dual Algorithms for Empirical
  Composition Optimization

Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization

22 July 2019
Adithya M. Devraj
Jianshu Chen
ArXivPDFHTML

Papers citing "Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization"

4 / 4 papers shown
Title
Doubly Robust Instance-Reweighted Adversarial Training
Doubly Robust Instance-Reweighted Adversarial Training
Daouda Sow
Sen-Fon Lin
Zhangyang Wang
Yitao Liang
AAML
OOD
33
2
0
01 Aug 2023
Stability and Generalization of Stochastic Compositional Gradient
  Descent Algorithms
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
Minghao Yang
Xiyuan Wei
Tianbao Yang
Yiming Ying
40
1
0
07 Jul 2023
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave
  Saddle Point Problems without Strong Convexity
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity
S. Du
Wei Hu
58
120
0
05 Feb 2018
A Proximal Stochastic Gradient Method with Progressive Variance
  Reduction
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao
Tong Zhang
ODL
90
736
0
19 Mar 2014
1