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Accelerate Stochastic Subgradient Method by Leveraging Local Growth
  Condition

Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition

4 July 2016
Yi Tian Xu
Qihang Lin
Tianbao Yang
ArXivPDFHTML

Papers citing "Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition"

6 / 6 papers shown
Title
Characterization of Convex Objective Functions and Optimal Expected
  Convergence Rates for SGD
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
Marten van Dijk
Lam M. Nguyen
Phuong Ha Nguyen
Dzung Phan
28
6
0
09 Oct 2018
Closing the Generalization Gap of Adaptive Gradient Methods in Training
  Deep Neural Networks
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
Jinghui Chen
Dongruo Zhou
Yiqi Tang
Ziyan Yang
Yuan Cao
Quanquan Gu
ODL
13
192
0
18 Jun 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
124
1,198
0
16 Aug 2016
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than
  $O(1/ε)$
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/ε)O(1/ε)O(1/ε)
Yi Tian Xu
Yan Yan
Qihang Lin
Tianbao Yang
44
25
0
13 Jul 2016
Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its
  applications to linear convergence of first-order methods
Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods
Guoyin Li
Ting Kei Pong
102
288
0
09 Feb 2016
A Proximal Stochastic Gradient Method with Progressive Variance
  Reduction
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao
Tong Zhang
ODL
76
736
0
19 Mar 2014
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