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Optimistic mirror descent in saddle-point problems: Going the extra
  (gradient) mile

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

7 July 2018
P. Mertikopoulos
Bruno Lecouat
Houssam Zenati
Chuan-Sheng Foo
V. Chandrasekhar
Georgios Piliouras
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Papers citing "Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile"

4 / 54 papers shown
Title
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum
  Linear Quadratic Games
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games
Kaipeng Zhang
Zhuoran Yang
Tamer Basar
19
125
0
31 May 2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring
  for Minimax Problems
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems
Ernest K. Ryu
Kun Yuan
W. Yin
20
36
0
26 May 2019
Bandit learning in concave $N$-person games
Bandit learning in concave NNN-person games
Mario Bravo
David S. Leslie
P. Mertikopoulos
6
121
0
03 Oct 2018
First-order Methods Almost Always Avoid Saddle Points
First-order Methods Almost Always Avoid Saddle Points
J. Lee
Ioannis Panageas
Georgios Piliouras
Max Simchowitz
Michael I. Jordan
Benjamin Recht
ODL
93
82
0
20 Oct 2017
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